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 https://whatsmusic.de/frankien-interview-creating-the-singer-songwriter-genre-standing-against-racism-and-a-memorable-open-mic-episode/

Tuesday, February 23, 2021

Launch HN: Abacum (YC W21) – Easy collaboration and reporting for finance teams https://ift.tt/3pKswpdTHE RIGHT PEOPLE https://ift.tt/3keo158THE RIGHT PEOPLE https://ift.tt/3dMUXjQ https://ift.tt/3dMUXjQ

Launch HN: Abacum (YC W21) – Easy collaboration and reporting for finance teams Hi HN! We’re Jorge and Julio, cofounders of Abacum ( https://www.abacum.io/ ). We’re not sure how many fintech geeks like us are on HN but we’re very excited to launch to you guys anyway! Abacum makes it easier for Finance teams to access real-time data, collaborate and generate reports. Think of having all the operational and financial data modeled in one place, and of the Finance team easily sharing and collecting information for other teams to make faster, better decisions. Scale ups have unique finance needs. First, they have spent the last years growing unnaturally fast, held together by a mixture of google sheets, csv files, a disconnected tech stack and a lot of copy paste. Second, growing 4x a year means that historical data is out of date within 3 months. Finally, with so many channels to stay connected, it’s impossible to find where the Tech Lead shared that key assumption for the board forecast. Both Jorge and I have lived these experiences – we’ve spent too many long nights and days in number-crunching, without the proper time to analyze the data and to provide insights, becoming the key business partner we wanted. So yes, in the middle of the lockdown with 3 children each decided to leave everything to build the product we wish we had! Abacum can now connect to any data source, update a business plan automatically and give you finance specific tools to help you do what you need to. Think performance and pivot tables, cohort and waterfall graphs, and ways to easily collaborate. Our engine provides the flexibility of excel while minimizing human errors, reducing fears of breaking “the model” and scaling up to and past IPO size. We’re big believers that collaboration, and not the business model, needs to be placed at the center of the product. Everything we built in Abacum is easily shareable and built to be easily understood by non-finance professionals. Ask (or remind) others in your company to collaborate, be it for updating forecasts or commenting on reporting decks, right where the needed context is. We’ve also set up different workflows for customers to easily gather the data bottom-up from different teams. We are constantly looking to improve Abacum, so we’d love to hear any feedback, questions or wisdom you have to share with us! We’d love to show you (or anybody that you think may be interested) a 10′ demo of our product – please let us know and we’ll reach out. Thanks so much, HN! February 23, 2021 at 05:20AM

via Blogger https://ift.tt/3dMLc5c

(https://ift.tt/3dCnJ6L

Show HN: GPT-3 resources, examples, and use cases https://ift.tt/3sjIZCrTHE RIGHT PEOPLE https://ift.tt/3pMuDcaTHE RIGHT PEOPLE https://ift.tt/3keQFmA https://ift.tt/3keQFmA

Show HN: GPT-3 resources, examples, and use cases https://gpt3demo.com/ February 23, 2021 at 03:04AM

via Blogger https://ift.tt/3si3jnO

(https://ift.tt/3aNKKBO

Show HN: MobX-Style Observables in Svelte https://ift.tt/2ZELdjETHE RIGHT PEOPLE https://ift.tt/3usXLcaTHE RIGHT PEOPLE https://ift.tt/3qIYfZc https://ift.tt/3qIYfZc

Show HN: MobX-Style Observables in Svelte https://ift.tt/2NOUClW February 23, 2021 at 12:29AM

via Blogger https://ift.tt/3dFgKdu

(https://ift.tt/3kdWGjH

Show HN: Test your Gitlab CI Pipelines changes locally using Docker https://ift.tt/2ZG3VqT

Show HN: Test your Gitlab CI Pipelines changes locally using Docker https://ift.tt/3kfmpYU February 23, 2021 at 04:47AM

Launch HN: Abacum (YC W21) – Easy collaboration and reporting for finance teams https://ift.tt/3pKswpd

Launch HN: Abacum (YC W21) – Easy collaboration and reporting for finance teams Hi HN! We're Jorge and Julio, cofounders of Abacum ( https://www.abacum.io/ ). We're not sure how many fintech geeks like us are on HN but we're very excited to launch to you guys anyway! Abacum makes it easier for Finance teams to access real-time data, collaborate and generate reports. Think of having all the operational and financial data modeled in one place, and of the Finance team easily sharing and collecting information for other teams to make faster, better decisions. Scale ups have unique finance needs. First, they have spent the last years growing unnaturally fast, held together by a mixture of google sheets, csv files, a disconnected tech stack and a lot of copy paste. Second, growing 4x a year means that historical data is out of date within 3 months. Finally, with so many channels to stay connected, it's impossible to find where the Tech Lead shared that key assumption for the board forecast. Both Jorge and I have lived these experiences - we've spent too many long nights and days in number-crunching, without the proper time to analyze the data and to provide insights, becoming the key business partner we wanted. So yes, in the middle of the lockdown with 3 children each decided to leave everything to build the product we wish we had! Abacum can now connect to any data source, update a business plan automatically and give you finance specific tools to help you do what you need to. Think performance and pivot tables, cohort and waterfall graphs, and ways to easily collaborate. Our engine provides the flexibility of excel while minimizing human errors, reducing fears of breaking "the model" and scaling up to and past IPO size. We're big believers that collaboration, and not the business model, needs to be placed at the center of the product. Everything we built in Abacum is easily shareable and built to be easily understood by non-finance professionals. Ask (or remind) others in your company to collaborate, be it for updating forecasts or commenting on reporting decks, right where the needed context is. We've also set up different workflows for customers to easily gather the data bottom-up from different teams. We are constantly looking to improve Abacum, so we'd love to hear any feedback, questions or wisdom you have to share with us! We'd love to show you (or anybody that you think may be interested) a 10' demo of our product - please let us know and we'll reach out. Thanks so much, HN! February 23, 2021 at 05:20AM

Show HN: GPT-3 resources, examples, and use cases https://ift.tt/3sjIZCr

Show HN: GPT-3 resources, examples, and use cases https://gpt3demo.com/ February 23, 2021 at 03:04AM

Show HN: MobX-Style Observables in Svelte https://ift.tt/2ZELdjE

Show HN: MobX-Style Observables in Svelte https://ift.tt/2NOUClW February 23, 2021 at 12:29AM

Show HN: Constexpr.js https://ift.tt/3pJSF7MTHE RIGHT PEOPLE https://ift.tt/3dzYK4dTHE RIGHT PEOPLE https://ift.tt/3qNUyBv https://ift.tt/3qNUyBvTHE RIGHT PEOPLE https://ift.tt/2P3lrDETHE RIGHT PEOPLE https://ift.tt/2MeDtSa https://ift.tt/2MeDtSa

Show HN: Constexpr.js https://ift.tt/3k8FITJ February 22, 2021 at 06:24PM

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Show HN: Community of professionals, with satisfaction and transparency at core https://ift.tt/37E1da0THE RIGHT PEOPLE https://ift.tt/3sgEwjWTHE RIGHT PEOPLE https://ift.tt/3shQ5Hv https://ift.tt/3shQ5HvTHE RIGHT PEOPLE https://ift.tt/3aKh74ETHE RIGHT PEOPLE https://ift.tt/3spKijv https://ift.tt/3spKijv

Show HN: Community of professionals, with satisfaction and transparency at core https://app.everi.one/ February 22, 2021 at 05:58PM

via Blogger https://ift.tt/2P4v05h

(https://ift.tt/3upVOx2

via Blogger https://ift.tt/3pOSwjg

(https://ift.tt/3aI1vP2

Show HN: Constexpr.js https://ift.tt/3pJSF7MTHE RIGHT PEOPLE https://ift.tt/3dzYK4dTHE RIGHT PEOPLE https://ift.tt/3qNUyBv https://ift.tt/3qNUyBv

Show HN: Constexpr.js https://ift.tt/3k8FITJ February 22, 2021 at 06:24PM

via Blogger https://ift.tt/3uzbi1Q

(https://ift.tt/3kb9sPS

Show HN: Community of professionals, with satisfaction and transparency at core https://ift.tt/37E1da0THE RIGHT PEOPLE https://ift.tt/3sgEwjWTHE RIGHT PEOPLE https://ift.tt/3shQ5Hv https://ift.tt/3shQ5Hv

Show HN: Community of professionals, with satisfaction and transparency at core https://app.everi.one/ February 22, 2021 at 05:58PM

via Blogger https://ift.tt/2P4v05h

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Show HN: Constexpr.js https://ift.tt/3pJSF7M

Show HN: Constexpr.js https://ift.tt/3k8FITJ February 22, 2021 at 06:24PM

Show HN: Community of professionals, with satisfaction and transparency at core https://ift.tt/37E1da0

Show HN: Community of professionals, with satisfaction and transparency at core https://app.everi.one/ February 22, 2021 at 05:58PM

Monday, February 22, 2021

Launch HN: H3X (YC W21) – High power density electric aircraft motors https://ift.tt/3qERuaO

Launch HN: H3X (YC W21) – High power density electric aircraft motors Hey HN! I’m Jason, one of the co-founders at H3X ( https://www.h3x.tech ). We are building the lightest electric propulsion systems in the world. Our first product is a 250kW (330HP) integrated motor drive in a 18kg (40lb) package. It combines the electric motor, inverter, and gearbox into a single unit, resulting in an ultra-high-power density solution for electric aircraft (and other mass sensitive applications). In terms of electrification, we believe the aircraft industry is where automotive was ten years ago. There are many companies working on eVTOL and single-seaters, but very few are working on large commercial single-aisle electric aircraft such as a 737. This class of aircraft is absolutely critical to electrify as it accounts for the most passenger-miles [1] and is the biggest slice of the pie in terms of aviation emissions. Beyond the environmental impact, there are huge potential cost savings from both fuel (or lack thereof) and reduced maintenance for airlines. Aircraft are very mass sensitive so there are two main technology challenges that need to be solved to enable this class of electric aviation – (1) High energy density and efficient energy storage (batteries, hydrogen fuel cells, etc.) (2) Light, efficient, and high-power density electric propulsion systems (electric motors, power electronics, gearbox) There are many people working on (1) and great strides are being made [2][3]. We are focused on solving (2). A study done by the DOE determined that for a 737 to complete a five-hour flight, the propulsion system must be >12 kW/kg [4]. Today, best-in-class systems have a power density of 3-4 kW/kg. With our first product, we are targeting 13 kW/kg, making it an attractive solution for near-term Advanced Air Mobility (AAM) applications as well as an enabling technology for the aviation industry to enter the next stage of electrification. There are some cool things we are doing with the electromagnetics, power electronics, and the integration between the systems to get to the 13 kW/kg. There is not a single magic bullet, but rather a combination of multiple technological advances - 3D printed copper stator coils, high frequency SiC power electronics, and a synergistic cooling system to name a few. Our origins in electrification stem back to our college days where we built Formula-style electric racecars (s/o to Wisconsin Racing FSAE!). During year 1 of the program, we got so fed up with our COTS motors and inverters, we decided to go clean slate and build our own from the ground up the following year. Those were super happy fun times. Lots of dead IGBTs and all-nighters in the shop, but in the end, we got everything working and delivered! It was a true test of resilience and taught us how to GSD. Great preparation for starting a company. This led us to grad school and it became apparent during this time that the electric aircraft industry was a sleeping giant ready to be woken. We felt uniquely positioned to capitalize on this opportunity, so after about a year in industry, we left our full-time jobs and went all in. We’ve got a long road ahead - aviation is tough, there’s no denying that. In addition to the engineering challenges, there are also major certification barriers. However, CO2 is a serious problem and right now the major aviation players don’t have a compelling plan to meet the goals laid out in the Paris Agreement. Innovation needs to come from the outside and that’s what we’re doing at H3X. I’d love to hear your guys thoughts and would be happy to answer any questions you have. Sources: [1] https://ift.tt/2NrNzQc [2] https://ift.tt/2MjLy8o... [3] https://hypoint.com/ , https://ift.tt/3hRFbEC [4] ASCEND DE-FOA-0002238 February 22, 2021 at 06:11AM

Show HN: Magic Login – Passwordless login and transactional emails as a service https://ift.tt/3updGI8

Show HN: Magic Login – Passwordless login and transactional emails as a service https://magiclogin.net February 22, 2021 at 05:09AM

Show HN: Building a Binary Counter https://ift.tt/3um45llTHE RIGHT PEOPLE https://ift.tt/3uvujCiTHE RIGHT PEOPLE https://ift.tt/3ukn3cf https://ift.tt/3ukn3cfTHE RIGHT PEOPLE https://ift.tt/3briWmbTHE RIGHT PEOPLE https://ift.tt/3pLdgIG https://ift.tt/3pLdgIGTHE RIGHT PEOPLE https://ift.tt/3qJLOfATHE RIGHT PEOPLE https://ift.tt/3pIiR2D https://ift.tt/3pIiR2DTHE RIGHT PEOPLE https://ift.tt/3aIm1zaTHE RIGHT PEOPLE https://ift.tt/2OQn47p https://ift.tt/2OQn47p

Show HN: Building a Binary Counter https://ift.tt/3dB6FhI February 21, 2021 at 05:33PM

via Blogger https://ift.tt/37DJwHE

(https://ift.tt/3ulhrP6

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via Blogger https://ift.tt/3qINK85

(https://ift.tt/2OQn4Er

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/3dAi4OQTHE RIGHT PEOPLE https://ift.tt/3aEactuTHE RIGHT PEOPLE https://ift.tt/3pGZkzl https://ift.tt/3pGZkzlTHE RIGHT PEOPLE https://ift.tt/2Mb6jmrTHE RIGHT PEOPLE https://ift.tt/3qUEqyp https://ift.tt/3qUEqypTHE RIGHT PEOPLE https://ift.tt/3bx9r4ZTHE RIGHT PEOPLE https://ift.tt/3qCInaF https://ift.tt/3qCInaFTHE RIGHT PEOPLE https://ift.tt/3bnFkwETHE RIGHT PEOPLE https://ift.tt/3bvrQim https://ift.tt/3bvrQim

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/2NGfFnG February 21, 2021 at 03:59PM

via Blogger https://ift.tt/2ZAw2Yv

(https://ift.tt/3sgWMJW

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(https://ift.tt/3aGQ0qV

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(https://ift.tt/2ZFLOkV

via Blogger https://ift.tt/3ulq4Jc

(https://ift.tt/2MhqlvM

Show HN: DeKarmaHN, a Chrome extension to hide karma and more https://ift.tt/3btlNuBTHE RIGHT PEOPLE https://ift.tt/3pAvH2MTHE RIGHT PEOPLE https://ift.tt/3kc6oTA https://ift.tt/3kc6oTATHE RIGHT PEOPLE https://ift.tt/3kiJGcATHE RIGHT PEOPLE https://ift.tt/3pJIArj https://ift.tt/3pJIArj

Show HN: DeKarmaHN, a Chrome extension to hide karma and more https://ift.tt/3aDQ9vg February 21, 2021 at 07:23PM

via Blogger https://ift.tt/2NMX8Jo

(https://ift.tt/3aGDIij

via Blogger https://ift.tt/2ZAmYTL

(https://ift.tt/3ul2fBp

Show HN: ProSudoku – Play Sudoku with Apple Pencil on iPad https://ift.tt/2Nw425XTHE RIGHT PEOPLE https://ift.tt/3kbKdwJTHE RIGHT PEOPLE https://ift.tt/2Maotom https://ift.tt/2MaotomTHE RIGHT PEOPLE https://ift.tt/3aCU6AuTHE RIGHT PEOPLE https://ift.tt/2ZJNGcl https://ift.tt/2ZJNGcl

Show HN: ProSudoku – Play Sudoku with Apple Pencil on iPad https://ift.tt/3pHkAVy February 21, 2021 at 05:58PM

via Blogger https://ift.tt/3ulsB6s

(https://ift.tt/37DObJo

via Blogger https://ift.tt/37CCMcP

(https://ift.tt/3brWXLF

Show HN: Building a Binary Counter https://ift.tt/3um45llTHE RIGHT PEOPLE https://ift.tt/3uvujCiTHE RIGHT PEOPLE https://ift.tt/3ukn3cf https://ift.tt/3ukn3cfTHE RIGHT PEOPLE https://ift.tt/3briWmbTHE RIGHT PEOPLE https://ift.tt/3pLdgIG https://ift.tt/3pLdgIGTHE RIGHT PEOPLE https://ift.tt/3qJLOfATHE RIGHT PEOPLE https://ift.tt/3pIiR2D https://ift.tt/3pIiR2D

Show HN: Building a Binary Counter https://ift.tt/3dB6FhI February 21, 2021 at 05:33PM

via Blogger https://ift.tt/37DJwHE

(https://ift.tt/3ulhrP6

via Blogger https://ift.tt/3qLhxgz

(https://ift.tt/3blgg9m

via Blogger https://ift.tt/3kbaJq0

(https://ift.tt/3uoy2kM

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/3dAi4OQTHE RIGHT PEOPLE https://ift.tt/3aEactuTHE RIGHT PEOPLE https://ift.tt/3pGZkzl https://ift.tt/3pGZkzlTHE RIGHT PEOPLE https://ift.tt/2Mb6jmrTHE RIGHT PEOPLE https://ift.tt/3qUEqyp https://ift.tt/3qUEqypTHE RIGHT PEOPLE https://ift.tt/3bx9r4ZTHE RIGHT PEOPLE https://ift.tt/3qCInaF https://ift.tt/3qCInaF

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/2NGfFnG February 21, 2021 at 03:59PM

via Blogger https://ift.tt/2ZAw2Yv

(https://ift.tt/3sgWMJW

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(https://ift.tt/3aGQ0qV

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(https://ift.tt/2ZFLOkV

Show HN: DeKarmaHN, a Chrome extension to hide karma and more https://ift.tt/3btlNuBTHE RIGHT PEOPLE https://ift.tt/3pAvH2MTHE RIGHT PEOPLE https://ift.tt/3kc6oTA https://ift.tt/3kc6oTA

Show HN: DeKarmaHN, a Chrome extension to hide karma and more https://ift.tt/3aDQ9vg February 21, 2021 at 07:23PM

via Blogger https://ift.tt/2NMX8Jo

(https://ift.tt/3aGDIij

Show HN: ProSudoku – Play Sudoku with Apple Pencil on iPad https://ift.tt/2Nw425XTHE RIGHT PEOPLE https://ift.tt/3kbKdwJTHE RIGHT PEOPLE https://ift.tt/2Maotom https://ift.tt/2Maotom

Show HN: ProSudoku – Play Sudoku with Apple Pencil on iPad https://ift.tt/3pHkAVy February 21, 2021 at 05:58PM

via Blogger https://ift.tt/3ulsB6s

(https://ift.tt/37DObJo

Show HN: Building a Binary Counter https://ift.tt/3um45llTHE RIGHT PEOPLE https://ift.tt/3uvujCiTHE RIGHT PEOPLE https://ift.tt/3ukn3cf https://ift.tt/3ukn3cfTHE RIGHT PEOPLE https://ift.tt/3briWmbTHE RIGHT PEOPLE https://ift.tt/3pLdgIG https://ift.tt/3pLdgIG

Show HN: Building a Binary Counter https://ift.tt/3dB6FhI February 21, 2021 at 05:33PM

via Blogger https://ift.tt/37DJwHE

(https://ift.tt/3ulhrP6

via Blogger https://ift.tt/3qLhxgz

(https://ift.tt/3blgg9m

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/3dAi4OQTHE RIGHT PEOPLE https://ift.tt/3aEactuTHE RIGHT PEOPLE https://ift.tt/3pGZkzl https://ift.tt/3pGZkzlTHE RIGHT PEOPLE https://ift.tt/2Mb6jmrTHE RIGHT PEOPLE https://ift.tt/3qUEqyp https://ift.tt/3qUEqyp

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/2NGfFnG February 21, 2021 at 03:59PM

via Blogger https://ift.tt/2ZAw2Yv

(https://ift.tt/3sgWMJW

via Blogger https://ift.tt/3ujxvRl

(https://ift.tt/3aGQ0qV

Show HN: DeKarmaHN, a Chrome extension to hide karma and more https://ift.tt/3btlNuB

Show HN: DeKarmaHN, a Chrome extension to hide karma and more https://ift.tt/3aDQ9vg February 21, 2021 at 07:23PM

Show HN: ProSudoku – Play Sudoku with Apple Pencil on iPad https://ift.tt/2Nw425X

Show HN: ProSudoku – Play Sudoku with Apple Pencil on iPad https://ift.tt/3pHkAVy February 21, 2021 at 05:58PM

Show HN: Building a Binary Counter https://ift.tt/3um45llTHE RIGHT PEOPLE https://ift.tt/3uvujCiTHE RIGHT PEOPLE https://ift.tt/3ukn3cf https://ift.tt/3ukn3cf

Show HN: Building a Binary Counter https://ift.tt/3dB6FhI February 21, 2021 at 05:33PM

via Blogger https://ift.tt/37DJwHE

(https://ift.tt/3ulhrP6

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/3dAi4OQTHE RIGHT PEOPLE https://ift.tt/3aEactuTHE RIGHT PEOPLE https://ift.tt/3pGZkzl https://ift.tt/3pGZkzl

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/2NGfFnG February 21, 2021 at 03:59PM

via Blogger https://ift.tt/2ZAw2Yv

(https://ift.tt/3sgWMJW

Show HN: Building a Binary Counter https://ift.tt/3um45ll

Show HN: Building a Binary Counter https://ift.tt/3dB6FhI February 21, 2021 at 05:33PM

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/3dAi4OQ

Show HN: Turn scripts into fine-tuned voices via Wiki markups https://ift.tt/2NGfFnG February 21, 2021 at 03:59PM

Sunday, February 21, 2021

Show HN: Go-FrodoKEM a Practical quantum-secure key encapsulation in Go https://ift.tt/3kl6W9XTHE RIGHT PEOPLE https://ift.tt/3uiZX5QTHE RIGHT PEOPLE https://ift.tt/2MaOd41 https://ift.tt/2MaOd41

Show HN: Go-FrodoKEM a Practical quantum-secure key encapsulation in Go https://ift.tt/3duueZr February 21, 2021 at 03:09AM

via Blogger https://ift.tt/3pJZEgF

(https://ift.tt/3qKc3m8

Show HN: Write plain SQL, generate Typescript types of result row and parameters https://ift.tt/3dxNzZHTHE RIGHT PEOPLE https://ift.tt/2OY8A5ETHE RIGHT PEOPLE https://ift.tt/2ZCTzYU https://ift.tt/2ZCTzYU

Show HN: Write plain SQL, generate Typescript types of result row and parameters https://ift.tt/2ZCKAa4 February 20, 2021 at 10:16PM

via Blogger https://ift.tt/3sjMnxj

(https://ift.tt/2Mh63Ta

Show HN: Python Wheel Obfuscator https://ift.tt/3sigR2rTHE RIGHT PEOPLE https://ift.tt/2ZzcHXVTHE RIGHT PEOPLE https://ift.tt/3buzf1x https://ift.tt/3buzf1x

Show HN: Python Wheel Obfuscator https://ift.tt/2NogzZ6 February 20, 2021 at 11:26PM

via Blogger https://ift.tt/3uiZQaq

(https://ift.tt/3dzg4q0

Show HN: CompreFace is a free and open-source face recognition software https://ift.tt/37zTwS0

Show HN: CompreFace is a free and open-source face recognition software https://ift.tt/37zw4nT February 21, 2021 at 07:18AM

Show HN: Force Directed Graph of Singapore MRT and LRT Networks https://ift.tt/3sbyoJKTHE RIGHT PEOPLE https://ift.tt/3qGyXeiTHE RIGHT PEOPLE https://ift.tt/3aESnun https://ift.tt/3aESnun

Show HN: Force Directed Graph of Singapore MRT and LRT Networks https://ift.tt/3kaKAHK February 21, 2021 at 12:42AM

via Blogger https://ift.tt/3sc2SLI

(https://ift.tt/3ueYCwZ

Show HN: Go-FrodoKEM a Practical quantum-secure key encapsulation in Go https://ift.tt/3kl6W9X

Show HN: Go-FrodoKEM a Practical quantum-secure key encapsulation in Go https://ift.tt/3duueZr February 21, 2021 at 03:09AM

Show HN: Write plain SQL, generate Typescript types of result row and parameters https://ift.tt/3dxNzZH

Show HN: Write plain SQL, generate Typescript types of result row and parameters https://ift.tt/2ZCKAa4 February 20, 2021 at 10:16PM

Show HN: Python Wheel Obfuscator https://ift.tt/3sigR2r

Show HN: Python Wheel Obfuscator https://ift.tt/2NogzZ6 February 20, 2021 at 11:26PM

Show HN: Force Directed Graph of Singapore MRT and LRT Networks https://ift.tt/3sbyoJK

Show HN: Force Directed Graph of Singapore MRT and LRT Networks https://ift.tt/3kaKAHK February 21, 2021 at 12:42AM

Show HN: Tape Machine https://ift.tt/3pCB5CATHE RIGHT PEOPLE https://ift.tt/3qLNPs0THE RIGHT PEOPLE https://ift.tt/3k68550 https://ift.tt/3k68550THE RIGHT PEOPLE https://ift.tt/2ZxxSJMTHE RIGHT PEOPLE https://ift.tt/2NuigEp https://ift.tt/2NuigEp

Show HN: Tape Machine https://www.youtube.com/watch?v=XlQkZrrQx3U&feature=youtu.be February 20, 2021 at 07:08PM

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Show HN: Jambook.io – A “don’t break the chain” dashboard for GitHub writing https://ift.tt/37wUPRITHE RIGHT PEOPLE https://ift.tt/3boRCEZTHE RIGHT PEOPLE https://ift.tt/3aEhD48 https://ift.tt/3aEhD48THE RIGHT PEOPLE https://ift.tt/3aFCQdTTHE RIGHT PEOPLE https://ift.tt/3k9x4o7 https://ift.tt/3k9x4o7

Show HN: Jambook.io – A “don’t break the chain” dashboard for GitHub writing https://www.jambook.io/ February 20, 2021 at 03:40PM

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(https://ift.tt/3dBQsZt

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(https://ift.tt/3aDVW44

Show HN: Peppa Peg – An Ultra Lightweight Peg Parser in ANSI C https://ift.tt/2ZBEsPqTHE RIGHT PEOPLE https://ift.tt/3ukrmV2THE RIGHT PEOPLE https://ift.tt/3sgqS0q https://ift.tt/3sgqS0qTHE RIGHT PEOPLE https://ift.tt/2ONftGHTHE RIGHT PEOPLE https://ift.tt/3pJbesy https://ift.tt/3pJbesy

Show HN: Peppa Peg – An Ultra Lightweight Peg Parser in ANSI C After reading the [PEG Parsers series] written by Guido van Rossum, I started thinking writing a PEG Parser in ANSI C. Here are the reasons: – It’s FUN. I’ve made several parser libraries, such as JSON, Mustache, Markdown, and I think I can take the challenge now. – I haven’t had any opportunity to work on an Open Source project written in ANSI C. – Having a PEG parser in ANSI C can benefit whoever is developing a parser, as adding C bindings for other programming languages are not too difficult. And after SIX months’ development, my project is now kinda feature complete. It’s named Peppa PEG and you can find it here: https://ift.tt/3aBmrqW I have learned quite a lot during the journey of creating it, such as gdb, valgrind, cmake, etc. And I wouldn’t make it to the end without learning from some awesome projects, such as pest.rs, cJSON, etc. Appreciate any feedbacks! Thank you! [PEG Parsers series]: https://ift.tt/2M0QQTs February 20, 2021 at 06:10PM

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Show HN: Tape Machine https://ift.tt/3pCB5CATHE RIGHT PEOPLE https://ift.tt/3qLNPs0THE RIGHT PEOPLE https://ift.tt/3k68550 https://ift.tt/3k68550

Show HN: Tape Machine https://www.youtube.com/watch?v=XlQkZrrQx3U&feature=youtu.be February 20, 2021 at 07:08PM

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Show HN: Jambook.io – A “don’t break the chain” dashboard for GitHub writing https://ift.tt/37wUPRITHE RIGHT PEOPLE https://ift.tt/3boRCEZTHE RIGHT PEOPLE https://ift.tt/3aEhD48 https://ift.tt/3aEhD48

Show HN: Jambook.io – A “don’t break the chain” dashboard for GitHub writing https://www.jambook.io/ February 20, 2021 at 03:40PM

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Show HN: Peppa Peg – An Ultra Lightweight Peg Parser in ANSI C https://ift.tt/2ZBEsPqTHE RIGHT PEOPLE https://ift.tt/3ukrmV2THE RIGHT PEOPLE https://ift.tt/3sgqS0q https://ift.tt/3sgqS0q

Show HN: Peppa Peg – An Ultra Lightweight Peg Parser in ANSI C After reading the [PEG Parsers series] written by Guido van Rossum, I started thinking writing a PEG Parser in ANSI C. Here are the reasons: – It’s FUN. I’ve made several parser libraries, such as JSON, Mustache, Markdown, and I think I can take the challenge now. – I haven’t had any opportunity to work on an Open Source project written in ANSI C. – Having a PEG parser in ANSI C can benefit whoever is developing a parser, as adding C bindings for other programming languages are not too difficult. And after SIX months’ development, my project is now kinda feature complete. It’s named Peppa PEG and you can find it here: https://ift.tt/3aBmrqW I have learned quite a lot during the journey of creating it, such as gdb, valgrind, cmake, etc. And I wouldn’t make it to the end without learning from some awesome projects, such as pest.rs, cJSON, etc. Appreciate any feedbacks! Thank you! [PEG Parsers series]: https://ift.tt/2M0QQTs February 20, 2021 at 06:10PM

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(https://ift.tt/3pEphj9

Show HN: Tape Machine https://ift.tt/3pCB5CA

Show HN: Tape Machine https://www.youtube.com/watch?v=XlQkZrrQx3U&feature=youtu.be February 20, 2021 at 07:08PM

Show HN: Jambook.io – A “don't break the chain” dashboard for GitHub writing https://ift.tt/37wUPRI

Show HN: Jambook.io – A “don't break the chain” dashboard for GitHub writing https://www.jambook.io/ February 20, 2021 at 03:40PM

Show HN: Peppa Peg – An Ultra Lightweight Peg Parser in ANSI C https://ift.tt/2ZBEsPq

Show HN: Peppa Peg – An Ultra Lightweight Peg Parser in ANSI C After reading the [PEG Parsers series] written by Guido van Rossum, I started thinking writing a PEG Parser in ANSI C. Here are the reasons: - It's FUN. I've made several parser libraries, such as JSON, Mustache, Markdown, and I think I can take the challenge now. - I haven't had any opportunity to work on an Open Source project written in ANSI C. - Having a PEG parser in ANSI C can benefit whoever is developing a parser, as adding C bindings for other programming languages are not too difficult. And after SIX months' development, my project is now kinda feature complete. It's named Peppa PEG and you can find it here: https://ift.tt/3aBmrqW I have learned quite a lot during the journey of creating it, such as gdb, valgrind, cmake, etc. And I wouldn't make it to the end without learning from some awesome projects, such as pest.rs, cJSON, etc. Appreciate any feedbacks! Thank you! [PEG Parsers series]: https://ift.tt/2M0QQTs February 20, 2021 at 06:10PM

Saturday, February 20, 2021

Show HN: Validatum – build fluent validation functions in .NET https://ift.tt/3udD2stTHE RIGHT PEOPLE https://ift.tt/3k9a8W2THE RIGHT PEOPLE https://ift.tt/3aB6LE0 https://ift.tt/3aB6LE0THE RIGHT PEOPLE https://ift.tt/37vgnhNTHE RIGHT PEOPLE https://ift.tt/3azAYDu https://ift.tt/3azAYDu

Show HN: Validatum – build fluent validation functions in .NET https://ift.tt/3s7cUOf February 19, 2021 at 03:43PM

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Show HN: Share your workstation setup and earn with Amazon Affiliate links https://ift.tt/3scmoYA

Show HN: Share your workstation setup and earn with Amazon Affiliate links https://ift.tt/3qPcn2Y February 19, 2021 at 06:44PM

Show HN: Split Keyboards Gallery https://ift.tt/3se815MTHE RIGHT PEOPLE https://ift.tt/3brlZdQTHE RIGHT PEOPLE https://ift.tt/3bg4fSA https://ift.tt/3bg4fSATHE RIGHT PEOPLE https://ift.tt/2Nn8ofMTHE RIGHT PEOPLE https://ift.tt/3qPjisY https://ift.tt/3qPjisY

Show HN: Split Keyboards Gallery https://ift.tt/3bjXGyn February 18, 2021 at 05:01AM

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Show HN: Validatum – build fluent validation functions in .NET https://ift.tt/3udD2stTHE RIGHT PEOPLE https://ift.tt/3k9a8W2THE RIGHT PEOPLE https://ift.tt/3aB6LE0 https://ift.tt/3aB6LE0

Show HN: Validatum – build fluent validation functions in .NET https://ift.tt/3s7cUOf February 19, 2021 at 03:43PM

via Blogger https://ift.tt/3bmdeln

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Show HN: ClubCircle – gradient borders and status badges for Clubhouse avatars https://ift.tt/3ayVZOsTHE RIGHT PEOPLE https://ift.tt/3udyQJjTHE RIGHT PEOPLE https://ift.tt/2ZxULge https://ift.tt/2ZxULgeTHE RIGHT PEOPLE https://ift.tt/2NG6ZReTHE RIGHT PEOPLE https://ift.tt/3s7zYwj https://ift.tt/3s7zYwj

Show HN: ClubCircle – gradient borders and status badges for Clubhouse avatars https://clubcircle.app February 19, 2021 at 01:23PM

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Show HN: Augmented Reality Route Setting for Climbing https://ift.tt/3bqGtU4THE RIGHT PEOPLE https://ift.tt/3ufdT0GTHE RIGHT PEOPLE https://ift.tt/3qGiRBl https://ift.tt/3qGiRBlTHE RIGHT PEOPLE https://ift.tt/2M6hT2bTHE RIGHT PEOPLE https://ift.tt/3uiBQEr https://ift.tt/3uiBQEr

Show HN: Augmented Reality Route Setting for Climbing https://www.youtube.com/watch?v=_z9797LFm4c February 19, 2021 at 10:35AM

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Show HN: Crypto Mining Pools Aggregator https://ift.tt/3uc77J0THE RIGHT PEOPLE https://ift.tt/3dws5fMTHE RIGHT PEOPLE https://ift.tt/3k6rnHd https://ift.tt/3k6rnHdTHE RIGHT PEOPLE https://ift.tt/2ZEsfJHTHE RIGHT PEOPLE https://ift.tt/3kdAOVC https://ift.tt/3kdAOVC

Show HN: Crypto Mining Pools Aggregator https://ift.tt/3azwIUD February 19, 2021 at 06:03AM

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Show HN: Split Keyboards Gallery https://ift.tt/3se815MTHE RIGHT PEOPLE https://ift.tt/3brlZdQTHE RIGHT PEOPLE https://ift.tt/3bg4fSA https://ift.tt/3bg4fSA

Show HN: Split Keyboards Gallery https://ift.tt/3bjXGyn February 18, 2021 at 05:01AM

via Blogger https://ift.tt/37x5Ylv

(https://ift.tt/3blSsm2

Show HN: Validatum – build fluent validation functions in .NET https://ift.tt/3udD2st

Show HN: Validatum – build fluent validation functions in .NET https://ift.tt/3s7cUOf February 19, 2021 at 03:43PM

Show HN: ClubCircle – gradient borders and status badges for Clubhouse avatars https://ift.tt/3ayVZOsTHE RIGHT PEOPLE https://ift.tt/3udyQJjTHE RIGHT PEOPLE https://ift.tt/2ZxULge https://ift.tt/2ZxULge

Show HN: ClubCircle – gradient borders and status badges for Clubhouse avatars https://clubcircle.app February 19, 2021 at 01:23PM

via Blogger https://ift.tt/3bomYLP

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Show HN: Augmented Reality Route Setting for Climbing https://ift.tt/3bqGtU4THE RIGHT PEOPLE https://ift.tt/3ufdT0GTHE RIGHT PEOPLE https://ift.tt/3qGiRBl https://ift.tt/3qGiRBl

Show HN: Augmented Reality Route Setting for Climbing https://www.youtube.com/watch?v=_z9797LFm4c February 19, 2021 at 10:35AM

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Show HN: Crypto Mining Pools Aggregator https://ift.tt/3uc77J0THE RIGHT PEOPLE https://ift.tt/3dws5fMTHE RIGHT PEOPLE https://ift.tt/3k6rnHd https://ift.tt/3k6rnHd

Show HN: Crypto Mining Pools Aggregator https://ift.tt/3azwIUD February 19, 2021 at 06:03AM

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(https://ift.tt/3k7s6I9

Friday, February 19, 2021

Show HN: Split Keyboards Gallery https://ift.tt/3se815M

Show HN: Split Keyboards Gallery https://ift.tt/3bjXGyn February 18, 2021 at 05:01AM

Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database https://ift.tt/2ZuqrTNTHE RIGHT PEOPLE https://ift.tt/37uGuVMTHE RIGHT PEOPLE https://ift.tt/3dsTaQS https://ift.tt/3dsTaQSTHE RIGHT PEOPLE https://ift.tt/3azvR68THE RIGHT PEOPLE https://ift.tt/3pzCb1W https://ift.tt/3pzCb1W

Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database Hi HN, Adam and Jorge here, and today we’re very excited to share MindsDB with you ( https://ift.tt/2UJWtY6 ). MindsDB AutoML Server is an open-source platform designed to accelerate machine learning workflows for people with data inside databases by introducing virtual AI tables. We allow you to create and consume machine learning models as regular database tables. Jorge and I have been friends for many years, having first met at college. We have previously founded and failed at another startup, but we stuck together as a team to start MindsDB. Initially a passion project, MindsDB began as an idea to help those who could not afford to hire a team of data scientists, which at the time was (and still is) very expensive. It has since grown into a thriving open-source community with contributors and users all over the globe. With the plethora of data available in databases today, predictive modeling can often be a pain, especially if you need to write complex applications for ingesting data, training encoders and embedders, writing sampling algorithms, training models, optimizing, scheduling, versioning, moving models into production environments, maintaining them and then having to explain the predictions and the degree of confidence… we knew there had to be a better way! We aim to steer you away from constantly reinventing the wheel by abstracting most of the unnecessary complexities around building, training, and deploying machine learning models. MindsDB provides you with two techniques for this: build and train models as simply as you would write an SQL query, and seamlessly “publish” and manage machine learning models as virtual tables inside your databases (we support Clickhouse, MariaDB, MySQL, PostgreSQL, and MSSQL. MongoDB is coming soon.) We also support getting data from other sources, such as Snowflake, s3, SQLite, and any excel, JSON, or CSV file. When we talk to our growing community, we find that they are using MindsDB for anything ranging from reducing financial risk in the payments sector to predicting in-app usage statistics – one user is even trying to predict the price of Bitcoin using sentiment analysis (we wish them luck). No matter what the use-case, what we hear most often is that the two most painful parts of the whole process are model generation (R&D) and/or moving the model into production. For those who already have models (i.e. who have already done the R&D part), we are launching the ability to bring your own models from frameworks like Pytorch, Tensorflow, scikit-learn, Keras, XGBoost, CatBoost, LightGBM, etc. directly into your database. If you’d like to try this experimental feature, you can sign-up here: ( https://ift.tt/3uhw05U ) We currently have a handful of customers who pay us for support. However, we will soon be launching a cloud version of MindsDB for those who do not want to worry about DevOps, scalability, and managing GPU clusters. Nevertheless, MindsDB will always remain free and open-source, because democratizing machine learning is at the core of every decision we make. We’re making good progress thanks to our open-source community and are also grateful to have the backing of the founders of MySQL & MariaDB. We would love your feedback and invite you to try it out. We’d also love to hear about your experience, so please share your feedback, thoughts, comments, and ideas below. https://ift.tt/3k6zsfm or https://mindsdb.com/ Thanks in advance, Adam & Jorge February 19, 2021 at 08:55AM

via Blogger https://ift.tt/3pCzjkE

(https://ift.tt/3dt30Co

via Blogger https://ift.tt/3dHdFK3

(https://ift.tt/3pB6Mw6

Launch HN: HiGeorge (YC W21) – Real-time data visualizations for public datasets https://ift.tt/2NGzfTMTHE RIGHT PEOPLE https://ift.tt/2ZKvRu5THE RIGHT PEOPLE https://ift.tt/3qGzeOk https://ift.tt/3qGzeOkTHE RIGHT PEOPLE https://ift.tt/3doGZ7QTHE RIGHT PEOPLE https://ift.tt/2ZudTM2 https://ift.tt/2ZudTM2

Launch HN: HiGeorge (YC W21) – Real-time data visualizations for public datasets Hi HN! Anuj here. My co-founder Amir (Aazo11) and I are building HiGeorge ( https://hi-george.com/ ). We make localized drag-and-drop data visualizations so that all publishers, even the small ones, can better leverage data in their storytelling. Think Tableau with all the necessary data attached. At the onset of the pandemic Amir and I were looking for local data on the spread of the virus. We visited the sites of large national newsrooms like the NYTimes and were impressed by the quality of data visualizations and maps, but they lacked the geographic granularity for our own neighborhood. We then turned to our local newsrooms but found they presented data in tables and lists that made it difficult to comprehend the virus’ spread and trends. We wondered why. After talking to local journalists and publishers, we found that newsrooms simply do not have the resources to make sense of large datasets. Public datasets are hard to clean, poorly structured, and constantly updated. One publisher explained to us that she would refresh her state health department’s website 5 times a day waiting for updated COVID data, then manually download a CSV and clean it in Excel. This process could take hours, and it needed to happen every day. This is where HiGeorge comes in. We clean and aggregate public datasets and turn them into auto-updating data visualizations that anyone can instantly use with a simple copy/paste. Our data visualizations can be drag-and-dropped into articles, allowing news publishers to offer compelling data content to their communities. Check out a few versions of what we’re doing with customers — COVID-19 data reporting at North Carolina Health News [1], COVID-19 vaccine site mapping at SFGATE [2], real-time crime reporting in Dallas, TX [3], and police use of force at Mission Local [4]. Today, HiGeorge works with dozens of newsrooms across the country. Our visualizations have driven a 2x increase in pageviews and a 75% increase in session duration for our partner publishers. We charge a monthly subscription for access to our data visualization library – a fraction of the cost of an in-house data engineer. In the long run, we are building HiGeorge so that it becomes the single place to collaborate on and publish data content. We’d love to hear from the HN community and we’ll be hanging out in the comments if you have any questions or feedback. [1] https://ift.tt/3k10ZPa… [2] https://ift.tt/3k8D6oL… [3] https://ift.tt/3aBfXbs… [4] https://ift.tt/2M5IVGZ February 19, 2021 at 07:57AM

via Blogger https://ift.tt/37uLnOF

(https://ift.tt/3udwjin

via Blogger https://ift.tt/2OQgwpn

(https://ift.tt/3qFW3Sf

Show HN: ClubCircle – gradient borders and status badges for Clubhouse avatars https://ift.tt/3ayVZOs

Show HN: ClubCircle – gradient borders and status badges for Clubhouse avatars https://clubcircle.app February 19, 2021 at 01:23PM

Show HN: Augmented Reality Route Setting for Climbing https://ift.tt/3bqGtU4

Show HN: Augmented Reality Route Setting for Climbing https://www.youtube.com/watch?v=_z9797LFm4c February 19, 2021 at 10:35AM

Show HN: Crypto Mining Pools Aggregator https://ift.tt/3uc77J0

Show HN: Crypto Mining Pools Aggregator https://ift.tt/3azwIUD February 19, 2021 at 06:03AM

Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database https://ift.tt/2ZuqrTNTHE RIGHT PEOPLE https://ift.tt/37uGuVMTHE RIGHT PEOPLE https://ift.tt/3dsTaQS https://ift.tt/3dsTaQS

Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database Hi HN, Adam and Jorge here, and today we’re very excited to share MindsDB with you ( https://ift.tt/2UJWtY6 ). MindsDB AutoML Server is an open-source platform designed to accelerate machine learning workflows for people with data inside databases by introducing virtual AI tables. We allow you to create and consume machine learning models as regular database tables. Jorge and I have been friends for many years, having first met at college. We have previously founded and failed at another startup, but we stuck together as a team to start MindsDB. Initially a passion project, MindsDB began as an idea to help those who could not afford to hire a team of data scientists, which at the time was (and still is) very expensive. It has since grown into a thriving open-source community with contributors and users all over the globe. With the plethora of data available in databases today, predictive modeling can often be a pain, especially if you need to write complex applications for ingesting data, training encoders and embedders, writing sampling algorithms, training models, optimizing, scheduling, versioning, moving models into production environments, maintaining them and then having to explain the predictions and the degree of confidence… we knew there had to be a better way! We aim to steer you away from constantly reinventing the wheel by abstracting most of the unnecessary complexities around building, training, and deploying machine learning models. MindsDB provides you with two techniques for this: build and train models as simply as you would write an SQL query, and seamlessly “publish” and manage machine learning models as virtual tables inside your databases (we support Clickhouse, MariaDB, MySQL, PostgreSQL, and MSSQL. MongoDB is coming soon.) We also support getting data from other sources, such as Snowflake, s3, SQLite, and any excel, JSON, or CSV file. When we talk to our growing community, we find that they are using MindsDB for anything ranging from reducing financial risk in the payments sector to predicting in-app usage statistics – one user is even trying to predict the price of Bitcoin using sentiment analysis (we wish them luck). No matter what the use-case, what we hear most often is that the two most painful parts of the whole process are model generation (R&D) and/or moving the model into production. For those who already have models (i.e. who have already done the R&D part), we are launching the ability to bring your own models from frameworks like Pytorch, Tensorflow, scikit-learn, Keras, XGBoost, CatBoost, LightGBM, etc. directly into your database. If you’d like to try this experimental feature, you can sign-up here: ( https://ift.tt/3uhw05U ) We currently have a handful of customers who pay us for support. However, we will soon be launching a cloud version of MindsDB for those who do not want to worry about DevOps, scalability, and managing GPU clusters. Nevertheless, MindsDB will always remain free and open-source, because democratizing machine learning is at the core of every decision we make. We’re making good progress thanks to our open-source community and are also grateful to have the backing of the founders of MySQL & MariaDB. We would love your feedback and invite you to try it out. We’d also love to hear about your experience, so please share your feedback, thoughts, comments, and ideas below. https://ift.tt/3k6zsfm or https://mindsdb.com/ Thanks in advance, Adam & Jorge February 19, 2021 at 08:55AM

via Blogger https://ift.tt/3pCzjkE

(https://ift.tt/3dt30Co

Launch HN: HiGeorge (YC W21) – Real-time data visualizations for public datasets https://ift.tt/2NGzfTMTHE RIGHT PEOPLE https://ift.tt/2ZKvRu5THE RIGHT PEOPLE https://ift.tt/3qGzeOk https://ift.tt/3qGzeOk

Launch HN: HiGeorge (YC W21) – Real-time data visualizations for public datasets Hi HN! Anuj here. My co-founder Amir (Aazo11) and I are building HiGeorge ( https://hi-george.com/ ). We make localized drag-and-drop data visualizations so that all publishers, even the small ones, can better leverage data in their storytelling. Think Tableau with all the necessary data attached. At the onset of the pandemic Amir and I were looking for local data on the spread of the virus. We visited the sites of large national newsrooms like the NYTimes and were impressed by the quality of data visualizations and maps, but they lacked the geographic granularity for our own neighborhood. We then turned to our local newsrooms but found they presented data in tables and lists that made it difficult to comprehend the virus’ spread and trends. We wondered why. After talking to local journalists and publishers, we found that newsrooms simply do not have the resources to make sense of large datasets. Public datasets are hard to clean, poorly structured, and constantly updated. One publisher explained to us that she would refresh her state health department’s website 5 times a day waiting for updated COVID data, then manually download a CSV and clean it in Excel. This process could take hours, and it needed to happen every day. This is where HiGeorge comes in. We clean and aggregate public datasets and turn them into auto-updating data visualizations that anyone can instantly use with a simple copy/paste. Our data visualizations can be drag-and-dropped into articles, allowing news publishers to offer compelling data content to their communities. Check out a few versions of what we’re doing with customers — COVID-19 data reporting at North Carolina Health News [1], COVID-19 vaccine site mapping at SFGATE [2], real-time crime reporting in Dallas, TX [3], and police use of force at Mission Local [4]. Today, HiGeorge works with dozens of newsrooms across the country. Our visualizations have driven a 2x increase in pageviews and a 75% increase in session duration for our partner publishers. We charge a monthly subscription for access to our data visualization library – a fraction of the cost of an in-house data engineer. In the long run, we are building HiGeorge so that it becomes the single place to collaborate on and publish data content. We’d love to hear from the HN community and we’ll be hanging out in the comments if you have any questions or feedback. [1] https://ift.tt/3k10ZPa… [2] https://ift.tt/3k8D6oL… [3] https://ift.tt/3aBfXbs… [4] https://ift.tt/2M5IVGZ February 19, 2021 at 07:57AM

via Blogger https://ift.tt/37uLnOF

(https://ift.tt/3udwjin

Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database https://ift.tt/2ZuqrTN

Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database Hi HN, Adam and Jorge here, and today we’re very excited to share MindsDB with you ( https://ift.tt/2UJWtY6 ). MindsDB AutoML Server is an open-source platform designed to accelerate machine learning workflows for people with data inside databases by introducing virtual AI tables. We allow you to create and consume machine learning models as regular database tables. Jorge and I have been friends for many years, having first met at college. We have previously founded and failed at another startup, but we stuck together as a team to start MindsDB. Initially a passion project, MindsDB began as an idea to help those who could not afford to hire a team of data scientists, which at the time was (and still is) very expensive. It has since grown into a thriving open-source community with contributors and users all over the globe. With the plethora of data available in databases today, predictive modeling can often be a pain, especially if you need to write complex applications for ingesting data, training encoders and embedders, writing sampling algorithms, training models, optimizing, scheduling, versioning, moving models into production environments, maintaining them and then having to explain the predictions and the degree of confidence… we knew there had to be a better way! We aim to steer you away from constantly reinventing the wheel by abstracting most of the unnecessary complexities around building, training, and deploying machine learning models. MindsDB provides you with two techniques for this: build and train models as simply as you would write an SQL query, and seamlessly “publish” and manage machine learning models as virtual tables inside your databases (we support Clickhouse, MariaDB, MySQL, PostgreSQL, and MSSQL. MongoDB is coming soon.) We also support getting data from other sources, such as Snowflake, s3, SQLite, and any excel, JSON, or CSV file. When we talk to our growing community, we find that they are using MindsDB for anything ranging from reducing financial risk in the payments sector to predicting in-app usage statistics - one user is even trying to predict the price of Bitcoin using sentiment analysis (we wish them luck). No matter what the use-case, what we hear most often is that the two most painful parts of the whole process are model generation (R&D) and/or moving the model into production. For those who already have models (i.e. who have already done the R&D part), we are launching the ability to bring your own models from frameworks like Pytorch, Tensorflow, scikit-learn, Keras, XGBoost, CatBoost, LightGBM, etc. directly into your database. If you’d like to try this experimental feature, you can sign-up here: ( https://ift.tt/3uhw05U ) We currently have a handful of customers who pay us for support. However, we will soon be launching a cloud version of MindsDB for those who do not want to worry about DevOps, scalability, and managing GPU clusters. Nevertheless, MindsDB will always remain free and open-source, because democratizing machine learning is at the core of every decision we make. We’re making good progress thanks to our open-source community and are also grateful to have the backing of the founders of MySQL & MariaDB. We would love your feedback and invite you to try it out. We’d also love to hear about your experience, so please share your feedback, thoughts, comments, and ideas below. https://ift.tt/3k6zsfm or https://mindsdb.com/ Thanks in advance, Adam & Jorge February 19, 2021 at 08:55AM

Launch HN: HiGeorge (YC W21) – Real-time data visualizations for public datasets https://ift.tt/2NGzfTM

Launch HN: HiGeorge (YC W21) – Real-time data visualizations for public datasets Hi HN! Anuj here. My co-founder Amir (Aazo11) and I are building HiGeorge ( https://hi-george.com/ ). We make localized drag-and-drop data visualizations so that all publishers, even the small ones, can better leverage data in their storytelling. Think Tableau with all the necessary data attached. At the onset of the pandemic Amir and I were looking for local data on the spread of the virus. We visited the sites of large national newsrooms like the NYTimes and were impressed by the quality of data visualizations and maps, but they lacked the geographic granularity for our own neighborhood. We then turned to our local newsrooms but found they presented data in tables and lists that made it difficult to comprehend the virus’ spread and trends. We wondered why. After talking to local journalists and publishers, we found that newsrooms simply do not have the resources to make sense of large datasets. Public datasets are hard to clean, poorly structured, and constantly updated. One publisher explained to us that she would refresh her state health department’s website 5 times a day waiting for updated COVID data, then manually download a CSV and clean it in Excel. This process could take hours, and it needed to happen every day. This is where HiGeorge comes in. We clean and aggregate public datasets and turn them into auto-updating data visualizations that anyone can instantly use with a simple copy/paste. Our data visualizations can be drag-and-dropped into articles, allowing news publishers to offer compelling data content to their communities. Check out a few versions of what we’re doing with customers -- COVID-19 data reporting at North Carolina Health News [1], COVID-19 vaccine site mapping at SFGATE [2], real-time crime reporting in Dallas, TX [3], and police use of force at Mission Local [4]. Today, HiGeorge works with dozens of newsrooms across the country. Our visualizations have driven a 2x increase in pageviews and a 75% increase in session duration for our partner publishers. We charge a monthly subscription for access to our data visualization library – a fraction of the cost of an in-house data engineer. In the long run, we are building HiGeorge so that it becomes the single place to collaborate on and publish data content. We’d love to hear from the HN community and we’ll be hanging out in the comments if you have any questions or feedback. [1] https://ift.tt/3k10ZPa... [2] https://ift.tt/3k8D6oL... [3] https://ift.tt/3aBfXbs... [4] https://ift.tt/2M5IVGZ February 19, 2021 at 07:57AM

Show HN: Archive as you browse, store locally and/or share with others via IPFS https://ift.tt/3qAQ01dTHE RIGHT PEOPLE https://ift.tt/3ucFtvuTHE RIGHT PEOPLE https://ift.tt/3qC0nBX https://ift.tt/3qC0nBXTHE RIGHT PEOPLE https://ift.tt/2ZrJaPITHE RIGHT PEOPLE https://ift.tt/3ueNYGs https://ift.tt/3ueNYGs

Show HN: Archive as you browse, store locally and/or share with others via IPFS https://archiveweb.page February 18, 2021 at 06:04PM

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Show HN: Archive as you browse, store locally and/or share with others via IPFS https://ift.tt/3qAQ01dTHE RIGHT PEOPLE https://ift.tt/3ucFtvuTHE RIGHT PEOPLE https://ift.tt/3qC0nBX https://ift.tt/3qC0nBX

Show HN: Archive as you browse, store locally and/or share with others via IPFS https://archiveweb.page February 18, 2021 at 06:04PM

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Show HN: Archive as you browse, store locally and/or share with others via IPFS https://ift.tt/3qAQ01d

Show HN: Archive as you browse, store locally and/or share with others via IPFS https://archiveweb.page February 18, 2021 at 06:04PM

Thursday, February 18, 2021

Show HN: Kalaksi: a social-network built on top of RSS https://ift.tt/3aue6VWTHE RIGHT PEOPLE https://ift.tt/3dpiGGJTHE RIGHT PEOPLE https://ift.tt/3dCZzJF https://ift.tt/3dCZzJFTHE RIGHT PEOPLE https://ift.tt/3bhZyYGTHE RIGHT PEOPLE https://ift.tt/2Na84kz https://ift.tt/2Na84kz

Show HN: Kalaksi: a social-network built on top of RSS https://www.kalaksi.com February 18, 2021 at 07:37AM

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Show HN: ScreenToVideo – Record your videos flawlessly https://ift.tt/2NbjODq

Show HN: ScreenToVideo – Record your videos flawlessly https://ift.tt/3bNnemf February 18, 2021 at 12:15PM

Launch HN: Ontop (YC W21) – Easily hire and pay remote workers in LATAM https://ift.tt/3s2MTj0THE RIGHT PEOPLE https://ift.tt/3dmX5yDTHE RIGHT PEOPLE https://ift.tt/3jZfkeZ https://ift.tt/3jZfkeZTHE RIGHT PEOPLE https://ift.tt/2Nlk2rxTHE RIGHT PEOPLE https://ift.tt/3dqIJNG https://ift.tt/3dqIJNG

Launch HN: Ontop (YC W21) – Easily hire and pay remote workers in LATAM Hi YC! We are Santiago Aparicio, Julian Torres and Jaime Abella and we are from Colombia. We are building Ontop (www.ontop.ai) to help companies do remote hiring and payouts, all the way from contract creation, to compliance documentation and easy money transfers. COVID-19 has taught us all that remote works. Our bet is that companies in the US and Europe will start hiring more people in LATAM because talent is increasing in quality at a fraction of price compared to what they can get elsewhere. Paying people in LATAM requires local knowledge to get the level of speed and compliance that workers need to get their money on time. We are building a solution so companies hiring in LATAM have to do less paperwork, can easily be compliant and disperse payments to different countries in a single place. In our previous startup Fitpal (multi gym membership in LATAM) we experienced the pain behind signing contracts, collecting documents and sending money to different countries. We had to pay hundreds of gyms in LATAM and were frustrated by the amount of time we spent doing administrative work, when we should have been thinking on how to hack our way to growth. We handle all paperwork, compliance and payments so onboarding new people is really easy. And most importantly, everything done legally, by the book, so that companies are always due diligence proof. Our solution is tailored for LATAM guaranteeing the best speed and compliance in the market. We want to hear your thoughts on our solution. We value feedback and case uses that you might have. Email us at founders@ontop.ai and we will personally give you a demo. February 18, 2021 at 04:58AM

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Show HN: Merge multiple PDFs into one using WebAssembly https://ift.tt/3s6ywtUTHE RIGHT PEOPLE https://ift.tt/3drwLDETHE RIGHT PEOPLE https://ift.tt/2ZuVr5W https://ift.tt/2ZuVr5W

Show HN: Merge multiple PDFs into one using WebAssembly http://localpdf.tech/ February 18, 2021 at 08:52AM

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Show HN: Create APIs for static datasets without writing a single line of code https://ift.tt/3pxS8W4THE RIGHT PEOPLE https://ift.tt/3k4yqjYTHE RIGHT PEOPLE https://ift.tt/3bjE5OR https://ift.tt/3bjE5OR

Show HN: Create APIs for static datasets without writing a single line of code https://ift.tt/3k7WYsb February 18, 2021 at 08:15AM

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Show HN: Kalaksi: a social-network built on top of RSS https://ift.tt/3aue6VWTHE RIGHT PEOPLE https://ift.tt/3dpiGGJTHE RIGHT PEOPLE https://ift.tt/3dCZzJF https://ift.tt/3dCZzJF

Show HN: Kalaksi: a social-network built on top of RSS https://www.kalaksi.com February 18, 2021 at 07:37AM

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(https://ift.tt/3qsQVkl

Launch HN: Ontop (YC W21) – Easily hire and pay remote workers in LATAM https://ift.tt/3s2MTj0THE RIGHT PEOPLE https://ift.tt/3dmX5yDTHE RIGHT PEOPLE https://ift.tt/3jZfkeZ https://ift.tt/3jZfkeZ

Launch HN: Ontop (YC W21) – Easily hire and pay remote workers in LATAM Hi YC! We are Santiago Aparicio, Julian Torres and Jaime Abella and we are from Colombia. We are building Ontop (www.ontop.ai) to help companies do remote hiring and payouts, all the way from contract creation, to compliance documentation and easy money transfers. COVID-19 has taught us all that remote works. Our bet is that companies in the US and Europe will start hiring more people in LATAM because talent is increasing in quality at a fraction of price compared to what they can get elsewhere. Paying people in LATAM requires local knowledge to get the level of speed and compliance that workers need to get their money on time. We are building a solution so companies hiring in LATAM have to do less paperwork, can easily be compliant and disperse payments to different countries in a single place. In our previous startup Fitpal (multi gym membership in LATAM) we experienced the pain behind signing contracts, collecting documents and sending money to different countries. We had to pay hundreds of gyms in LATAM and were frustrated by the amount of time we spent doing administrative work, when we should have been thinking on how to hack our way to growth. We handle all paperwork, compliance and payments so onboarding new people is really easy. And most importantly, everything done legally, by the book, so that companies are always due diligence proof. Our solution is tailored for LATAM guaranteeing the best speed and compliance in the market. We want to hear your thoughts on our solution. We value feedback and case uses that you might have. Email us at founders@ontop.ai and we will personally give you a demo. February 18, 2021 at 04:58AM

via Blogger https://ift.tt/3dCi8xB

(https://ift.tt/2ZreFt5

Show HN: Merge multiple PDFs into one using WebAssembly https://ift.tt/3s6ywtU

Show HN: Merge multiple PDFs into one using WebAssembly http://localpdf.tech/ February 18, 2021 at 08:52AM

Show HN: Create APIs for static datasets without writing a single line of code https://ift.tt/3pxS8W4

Show HN: Create APIs for static datasets without writing a single line of code https://ift.tt/3k7WYsb February 18, 2021 at 08:15AM

Show HN: Kalaksi: a social-network built on top of RSS https://ift.tt/3aue6VW

Show HN: Kalaksi: a social-network built on top of RSS https://www.kalaksi.com February 18, 2021 at 07:37AM

Launch HN: Ontop (YC W21) – Easily hire and pay remote workers in LATAM https://ift.tt/3s2MTj0

Launch HN: Ontop (YC W21) – Easily hire and pay remote workers in LATAM Hi YC! We are Santiago Aparicio, Julian Torres and Jaime Abella and we are from Colombia. We are building Ontop (www.ontop.ai) to help companies do remote hiring and payouts, all the way from contract creation, to compliance documentation and easy money transfers. COVID-19 has taught us all that remote works. Our bet is that companies in the US and Europe will start hiring more people in LATAM because talent is increasing in quality at a fraction of price compared to what they can get elsewhere. Paying people in LATAM requires local knowledge to get the level of speed and compliance that workers need to get their money on time. We are building a solution so companies hiring in LATAM have to do less paperwork, can easily be compliant and disperse payments to different countries in a single place. In our previous startup Fitpal (multi gym membership in LATAM) we experienced the pain behind signing contracts, collecting documents and sending money to different countries. We had to pay hundreds of gyms in LATAM and were frustrated by the amount of time we spent doing administrative work, when we should have been thinking on how to hack our way to growth. We handle all paperwork, compliance and payments so onboarding new people is really easy. And most importantly, everything done legally, by the book, so that companies are always due diligence proof. Our solution is tailored for LATAM guaranteeing the best speed and compliance in the market. We want to hear your thoughts on our solution. We value feedback and case uses that you might have. Email us at founders@ontop.ai and we will personally give you a demo. February 18, 2021 at 04:58AM

Launch HN: Datrics (YC W21) – No-Code Analytics and ML for FinTech https://ift.tt/3beSuvYTHE RIGHT PEOPLE https://ift.tt/3au23b2THE RIGHT PEOPLE https://ift.tt/3dpJ439 https://ift.tt/3dpJ439THE RIGHT PEOPLE https://ift.tt/3ukECciTHE RIGHT PEOPLE https://ift.tt/3s67vqw https://ift.tt/3s67vqw

Launch HN: Datrics (YC W21) – No-Code Analytics and ML for FinTech Hey everyone, we’re Anton (avais), Kirill (Datkiri), and Volodymyr (vsofi), the founders of Datrics ( https://datrics.ai ). We help FinTech companies build and deploy machine learning models without writing code. We provide a visual tool to work with structured data by constructing a diagram of data manipulations from lego-like bricks, and then execute it all on a backend. This lets our users accomplish tasks that usually need a team of software engineers, data scientists, and DevOps. For instance, one of our customers is a consumer lending company that developed a new risk model using just our drag-and-drop interface. I used to lead a large data science consultancy team, being responsible for Financial Services (and Risks specifically). Our teams’ projects included end-to-end risk modeling, demand forecasting, and inventory management optimization, mostly requiring combined efforts from different technical teams and business units to be implemented. It usually took months of work to turn an idea into a complete solution, going through data snapshot gathering to cleansing to experimenting to working with engineering and DevOps teams to turn experiments in Jupyter notebooks into a complete application that worked in production. Moreover, even if the application and logic behind the scenes were really simple (could be just dozens or hundreds of lines of code for a core part), the process to bring this to end-users could take ages. We started thinking about possible solutions when a request from one of the Tier 1 banks appeared, which confirmed that we’re not alone in this vision: their problem was giving their “citizen data scientists” and “citizen developers” power to do data-driven work. In other words, work with the data and generate insights useful for business. That was the first time I’d heard the term “citizen data scientist”. Our users are now these citizen data scientists and developers, whom we’re giving the possibility to manipulate data, build apps, pipelines, and ML models with just nominal IT support. Datrics is designed not only to do ML without coding, but to give analysts and domain experts a drag and drop interface to perform queries, generate reports, and do forecasting in a visual way with nominal IT support. One of our core use cases is doing better credit risk modeling – create application scorecards based on ML or apply rule-based transactional fraud detection. For this use-case, we’ve developed intelligent bricks that allow you to do variables binning and scorecards in a visual way. Other use cases include reports and pivot tables on aggregating sales data from different countries in different formats or doing inventory optimization by forecasting the demand without knowing any programming language. We’re providing 50+ bricks to construct ETL pipelines and build models. There are some limitations – a finite number of pre-built building blocks that can be included in your app, but if there is no block that you need, you can easily build your own ( https://youtu.be/BQNFcZWwUC8 ). Datrics is initially cloud-native, but also can be installed on-prem for those customers who have corresponding security policy or setups. The underlying technology, the pipeline execution engine is rather complex and currently built on top of Dask, which gives Python scalability for big datasets. In the next release, we are going to support Pandas as well as to switch intelligently between small datasets for rapid prototyping and big datasets for pipeline deployments. We’re charging only for private deployments, so our web version is free: https://ift.tt/2Nfu1i1 . Try it to create your analytical applications with a machine learning component! We’ve put together a wiki ( https://wiki.datrics.ai ) to cover the major functionality, We are super-excited to hear your thoughts and feedback! We’re big believers in the power of Machine Learning and self-service analytics and are happy to discuss what you think of no-code approaches for doing ML and analytics generally as well as the availability of them for non-data scientists. Or anything you want to share in this space! February 18, 2021 at 12:12AM

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Launch HN: Datrics (YC W21) – No-Code Analytics and ML for FinTech https://ift.tt/3beSuvYTHE RIGHT PEOPLE https://ift.tt/3au23b2THE RIGHT PEOPLE https://ift.tt/3dpJ439 https://ift.tt/3dpJ439

Launch HN: Datrics (YC W21) – No-Code Analytics and ML for FinTech Hey everyone, we’re Anton (avais), Kirill (Datkiri), and Volodymyr (vsofi), the founders of Datrics ( https://datrics.ai ). We help FinTech companies build and deploy machine learning models without writing code. We provide a visual tool to work with structured data by constructing a diagram of data manipulations from lego-like bricks, and then execute it all on a backend. This lets our users accomplish tasks that usually need a team of software engineers, data scientists, and DevOps. For instance, one of our customers is a consumer lending company that developed a new risk model using just our drag-and-drop interface. I used to lead a large data science consultancy team, being responsible for Financial Services (and Risks specifically). Our teams’ projects included end-to-end risk modeling, demand forecasting, and inventory management optimization, mostly requiring combined efforts from different technical teams and business units to be implemented. It usually took months of work to turn an idea into a complete solution, going through data snapshot gathering to cleansing to experimenting to working with engineering and DevOps teams to turn experiments in Jupyter notebooks into a complete application that worked in production. Moreover, even if the application and logic behind the scenes were really simple (could be just dozens or hundreds of lines of code for a core part), the process to bring this to end-users could take ages. We started thinking about possible solutions when a request from one of the Tier 1 banks appeared, which confirmed that we’re not alone in this vision: their problem was giving their “citizen data scientists” and “citizen developers” power to do data-driven work. In other words, work with the data and generate insights useful for business. That was the first time I’d heard the term “citizen data scientist”. Our users are now these citizen data scientists and developers, whom we’re giving the possibility to manipulate data, build apps, pipelines, and ML models with just nominal IT support. Datrics is designed not only to do ML without coding, but to give analysts and domain experts a drag and drop interface to perform queries, generate reports, and do forecasting in a visual way with nominal IT support. One of our core use cases is doing better credit risk modeling – create application scorecards based on ML or apply rule-based transactional fraud detection. For this use-case, we’ve developed intelligent bricks that allow you to do variables binning and scorecards in a visual way. Other use cases include reports and pivot tables on aggregating sales data from different countries in different formats or doing inventory optimization by forecasting the demand without knowing any programming language. We’re providing 50+ bricks to construct ETL pipelines and build models. There are some limitations – a finite number of pre-built building blocks that can be included in your app, but if there is no block that you need, you can easily build your own ( https://youtu.be/BQNFcZWwUC8 ). Datrics is initially cloud-native, but also can be installed on-prem for those customers who have corresponding security policy or setups. The underlying technology, the pipeline execution engine is rather complex and currently built on top of Dask, which gives Python scalability for big datasets. In the next release, we are going to support Pandas as well as to switch intelligently between small datasets for rapid prototyping and big datasets for pipeline deployments. We’re charging only for private deployments, so our web version is free: https://ift.tt/2Nfu1i1 . Try it to create your analytical applications with a machine learning component! We’ve put together a wiki ( https://wiki.datrics.ai ) to cover the major functionality, We are super-excited to hear your thoughts and feedback! We’re big believers in the power of Machine Learning and self-service analytics and are happy to discuss what you think of no-code approaches for doing ML and analytics generally as well as the availability of them for non-data scientists. Or anything you want to share in this space! February 18, 2021 at 12:12AM

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(https://ift.tt/3s2iFg0

Launch HN: Datrics (YC W21) – No-Code Analytics and ML for FinTech https://ift.tt/3beSuvY

Launch HN: Datrics (YC W21) – No-Code Analytics and ML for FinTech Hey everyone, we're Anton (avais), Kirill (Datkiri), and Volodymyr (vsofi), the founders of Datrics ( https://datrics.ai ). We help FinTech companies build and deploy machine learning models without writing code. We provide a visual tool to work with structured data by constructing a diagram of data manipulations from lego-like bricks, and then execute it all on a backend. This lets our users accomplish tasks that usually need a team of software engineers, data scientists, and DevOps. For instance, one of our customers is a consumer lending company that developed a new risk model using just our drag-and-drop interface. I used to lead a large data science consultancy team, being responsible for Financial Services (and Risks specifically). Our teams’ projects included end-to-end risk modeling, demand forecasting, and inventory management optimization, mostly requiring combined efforts from different technical teams and business units to be implemented. It usually took months of work to turn an idea into a complete solution, going through data snapshot gathering to cleansing to experimenting to working with engineering and DevOps teams to turn experiments in Jupyter notebooks into a complete application that worked in production. Moreover, even if the application and logic behind the scenes were really simple (could be just dozens or hundreds of lines of code for a core part), the process to bring this to end-users could take ages. We started thinking about possible solutions when a request from one of the Tier 1 banks appeared, which confirmed that we’re not alone in this vision: their problem was giving their “citizen data scientists” and “citizen developers” power to do data-driven work. In other words, work with the data and generate insights useful for business. That was the first time I’d heard the term “citizen data scientist”. Our users are now these citizen data scientists and developers, whom we’re giving the possibility to manipulate data, build apps, pipelines, and ML models with just nominal IT support. Datrics is designed not only to do ML without coding, but to give analysts and domain experts a drag and drop interface to perform queries, generate reports, and do forecasting in a visual way with nominal IT support. One of our core use cases is doing better credit risk modeling - create application scorecards based on ML or apply rule-based transactional fraud detection. For this use-case, we’ve developed intelligent bricks that allow you to do variables binning and scorecards in a visual way. Other use cases include reports and pivot tables on aggregating sales data from different countries in different formats or doing inventory optimization by forecasting the demand without knowing any programming language. We’re providing 50+ bricks to construct ETL pipelines and build models. There are some limitations - a finite number of pre-built building blocks that can be included in your app, but if there is no block that you need, you can easily build your own ( https://youtu.be/BQNFcZWwUC8 ). Datrics is initially cloud-native, but also can be installed on-prem for those customers who have corresponding security policy or setups. The underlying technology, the pipeline execution engine is rather complex and currently built on top of Dask, which gives Python scalability for big datasets. In the next release, we are going to support Pandas as well as to switch intelligently between small datasets for rapid prototyping and big datasets for pipeline deployments. We’re charging only for private deployments, so our web version is free: https://ift.tt/2Nfu1i1 . Try it to create your analytical applications with a machine learning component! We've put together a wiki ( https://wiki.datrics.ai ) to cover the major functionality, We are super-excited to hear your thoughts and feedback! We're big believers in the power of Machine Learning and self-service analytics and are happy to discuss what you think of no-code approaches for doing ML and analytics generally as well as the availability of them for non-data scientists. Or anything you want to share in this space! February 18, 2021 at 12:12AM

Show HN: Job Alerts for the Freelancing Economy https://ift.tt/3awjXKuTHE RIGHT PEOPLE https://ift.tt/3u87i82THE RIGHT PEOPLE https://ift.tt/3aujgkI https://ift.tt/3aujgkITHE RIGHT PEOPLE https://ift.tt/3qxB6JhTHE RIGHT PEOPLE https://ift.tt/37nYu4r https://ift.tt/37nYu4r

Show HN: Job Alerts for the Freelancing Economy https://www.ginevar.com February 17, 2021 at 02:58PM

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Show HN: Job Alerts for the Freelancing Economy https://ift.tt/3awjXKuTHE RIGHT PEOPLE https://ift.tt/3u87i82THE RIGHT PEOPLE https://ift.tt/3aujgkI https://ift.tt/3aujgkI

Show HN: Job Alerts for the Freelancing Economy https://www.ginevar.com February 17, 2021 at 02:58PM

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Show HN: Job Alerts for the Freelancing Economy https://ift.tt/3awjXKu

Show HN: Job Alerts for the Freelancing Economy https://www.ginevar.com February 17, 2021 at 02:58PM

Wednesday, February 17, 2021

Show HN: DeltaCI: Bare Metal CI/CD with much faster builds https://ift.tt/37nyWEw

Show HN: DeltaCI: Bare Metal CI/CD with much faster builds https://deltaci.com February 17, 2021 at 07:17AM

Show HN: Commitlog – Simple CLI Changelog Generator Using Commit History https://ift.tt/3qv0AqGTHE RIGHT PEOPLE https://ift.tt/3jUWgP0THE RIGHT PEOPLE https://ift.tt/3av7FSC https://ift.tt/3av7FSC

Show HN: Commitlog – Simple CLI Changelog Generator Using Commit History https://ift.tt/34XukUa February 17, 2021 at 04:49AM

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(https://ift.tt/2NDn75P

Show HN: Mailoji – Emoji Email Addresses https://ift.tt/3dnjxYKTHE RIGHT PEOPLE https://ift.tt/3jY6MEXTHE RIGHT PEOPLE https://ift.tt/3ptXdim https://ift.tt/3ptXdim

Show HN: Mailoji – Emoji Email Addresses https://mailoji.com/ February 17, 2021 at 04:13AM

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(https://ift.tt/3poGSeM

Show HN: Book Launch – Writing Maintainable Unit Tests https://ift.tt/3aoNTrMTHE RIGHT PEOPLE https://ift.tt/3dlcX4MTHE RIGHT PEOPLE https://ift.tt/3biwosa https://ift.tt/3biwosa

Show HN: Book Launch – Writing Maintainable Unit Tests https://ift.tt/3apBtjp February 17, 2021 at 02:19AM

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Show HN: Experiments on Machine Translation in Pure Go https://ift.tt/3u5GMfCTHE RIGHT PEOPLE https://ift.tt/37og9J1THE RIGHT PEOPLE https://ift.tt/3jV6TBo https://ift.tt/3jV6TBo

Show HN: Experiments on Machine Translation in Pure Go https://ift.tt/3bfjqeQ February 17, 2021 at 12:47AM

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Show HN: Pure Golang PostgreSQL Parser powered by CockroachDB https://ift.tt/2M4D0SITHE RIGHT PEOPLE https://ift.tt/3jU1HO8THE RIGHT PEOPLE https://ift.tt/3pu1KBh https://ift.tt/3pu1KBh

Show HN: Pure Golang PostgreSQL Parser powered by CockroachDB https://ift.tt/3arMe4H February 17, 2021 at 12:43AM

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Show HN: A social platform with music in focus. Download the app https://ift.tt/37nIDmdTHE RIGHT PEOPLE https://ift.tt/3qsv1h2THE RIGHT PEOPLE https://ift.tt/2OPFhlP https://ift.tt/2OPFhlPTHE RIGHT PEOPLE https://ift.tt/3rYwDzBTHE RIGHT PEOPLE https://ift.tt/3u9ktpi https://ift.tt/3u9ktpi

Show HN: A social platform with music in focus. Download the app https://syncc.app/ February 17, 2021 at 01:46AM

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Show HN: Ray.so – Create beautiful images of your code https://ift.tt/3u6Ff8Z

Show HN: Ray.so – Create beautiful images of your code https://ray.so February 17, 2021 at 08:35AM

Show HN: Moneto – Cash planning tool for running a profitable business https://ift.tt/3at8mvD

Show HN: Moneto – Cash planning tool for running a profitable business https://ift.tt/3dik5Pq February 17, 2021 at 07:45AM