THE RIGHT PEOPLE: 2020 at 08:21AM

Show HN: Building the next-generation learning experience If you reflect a bit on how you learn, you will probably find that in order to acquire a skill or some level of expertise on a subject, you take 5 steps that make up your learning behaviour. 1. You find the learning materials for the subject. 2. You input these materials into your brain through reading and listening. 3. You process the new information through memorising and associating in order to construct a new thinking model. 4. You practise by solving problems that are designed for learning, or by having basic conversations in the case of learning languages. 5. You apply the new skill you just acquired and start creating values for the world with it. What Astrasum does is that we are hacking learning. We want to accelerate your learning by helping you become better and better at each one of these steps with our technology and growing community. We are still working to integrate AI and VR into our features, but they are already pretty cool. Try it out and if you find it helpful or fun, please share it with your friends as well! https://astrasum.com September 17, 2020 at 02:53AM

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Show HN: Embed Draw.io in Notion https://ift.tt/2HaGy2UTHE RIGHT PEOPLE https://ift.tt/35IZJefTHE RIGHT PEOPLE https://ift.tt/32EPtSn https://ift.tt/32EPtSn

Show HN: Embed Draw.io in Notion https://ift.tt/32F1p6G September 17, 2020 at 02:42AM

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Monday, September 7, 2020

Show HN: I wrote this to make note taking on YouTube effective https://ift.tt/3h3F32RTHE RIGHT PEOPLE https://ift.tt/3m0vTHNTHE RIGHT PEOPLE https://ift.tt/3m11wRR https://ift.tt/3m11wRR

Show HN: I wrote this to make note taking on YouTube effective https://ift.tt/3m8b0uC September 7, 2020 at 03:07AM

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Show HN: GitHub Action Changelog CI made using Python https://ift.tt/3h5eAllTHE RIGHT PEOPLE https://ift.tt/3m1EOZBTHE RIGHT PEOPLE https://ift.tt/3jMMm0y https://ift.tt/3jMMm0y

Show HN: GitHub Action Changelog CI made using Python https://ift.tt/3hYBtbn September 7, 2020 at 01:22AM

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Friday, August 14, 2020

Show HN: Photo Realistic QR-Codes https://ift.tt/30U6CqkTHE RIGHT PEOPLE https://ift.tt/3iEmBPoTHE RIGHT PEOPLE https://ift.tt/3aobC9X https://ift.tt/3aobC9X

Show HN: Photo Realistic QR-Codes https://ift.tt/2Q5wJEN August 14, 2020 at 07:06AM

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Show HN: A Genetic Algorithm library written in JavaScript https://ift.tt/3amQ1ibTHE RIGHT PEOPLE https://ift.tt/3kJytBnTHE RIGHT PEOPLE https://ift.tt/3kKEIVL https://ift.tt/3kKEIVL

Show HN: A Genetic Algorithm library written in JavaScript https://ift.tt/2eY8J14 August 14, 2020 at 07:05AM

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Show HN: Tweek – Super Fast To-Do Weekly Calendar App https://ift.tt/342xlD4THE RIGHT PEOPLE https://ift.tt/30WvzBJTHE RIGHT PEOPLE https://ift.tt/326y1F9 https://ift.tt/326y1F9

Show HN: Tweek – Super Fast To-Do Weekly Calendar App https://tweek.so August 14, 2020 at 06:43AM

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Show HN: Shellcaster, a terminal-based podcast manager in Rust https://ift.tt/3hamV8pTHE RIGHT PEOPLE https://ift.tt/2XYK2ecTHE RIGHT PEOPLE https://ift.tt/3aofSpQ https://ift.tt/3aofSpQ

Show HN: Shellcaster, a terminal-based podcast manager in Rust https://ift.tt/2WTaq98 August 14, 2020 at 05:55AM

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Wednesday, August 12, 2020

Show HN: dstack – an open-source tool to build data applications easily https://ift.tt/2XRaUgsTHE RIGHT PEOPLE https://ift.tt/30S1K5fTHE RIGHT PEOPLE https://ift.tt/31MbWLO https://ift.tt/31MbWLO

Show HN: dstack – an open-source tool to build data applications easily Dear HN, I am Riwaj, the cofounder of dstack.ai (https://ift.tt/3amrgmi). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot more open source data science frameworks than we integrated ourselves. For example, as a user, I want to push a matplotlib plot, a Tensorflow model, a plotly chart, a pandas dataframe, and I expect the presentation layer to fully-support it. Supporting all types of artifacts and providing all the tools to work with them solely seems to be a very challenging task. With this, we open-sourced the framework. Now you can build dstack locally, and run it on your servers, or in a cloud of your choice if that’s needed. More details on the project, how to use it, and the source code of the server can be found at the https://ift.tt/3fTKQqW repo. The client packages for Python and R are available at the https://ift.tt/33RCkXb and https://ift.tt/31YPmzN correspondingly. What’s next: User callbacks- so that application shows not just pre-calculated visualizations but also can fetch data from a store and process it in real-time. ML models- so that data scientists can publish a stack which binds together a pre-calculated ML model and user parameters Use cases- Support specific use cases that help data scientists to build data science models into data applications as fast as possible. We would be happy to get your feedback on the open-source framework and also get your opinion on what kind of use cases can be built on top of the framework? Thank you. August 12, 2020 at 06:14AM

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Show HN: Orchest – Data Science Pipelines https://ift.tt/3fPh5HOTHE RIGHT PEOPLE https://ift.tt/2CoSP1GTHE RIGHT PEOPLE https://ift.tt/30NQW7W https://ift.tt/30NQW7W

Show HN: Orchest – Data Science Pipelines Hello Hacker News! We are Rick & Yannick from Orchest (https://www.orchest.io – https://ift.tt/2XRxxBc). We’re building a visual pipeline tool for data scientists. The tool can be considered to be high-code because you write your own Python/R notebooks and scripts, but we manage the underlying infrastructure to make it ‘just work’. You can think of it as a simplified version of Kubeflow. We created Orchest to free data scientists from the tedious engineering related tasks of their job. Similar to how companies like Netflix, Uber and Booking.com support their data scientists with internal tooling and frameworks to increase productivity. When we worked as data scientists ourselves we noticed how heavily we had to depend on our software engineering skills to perform all kinds of tasks. From configuring cloud instances for distributed training, to optimizing the networking and storage for processing large amounts of data. We believe data scientists should be able to focus on the data and the domain specific challenges. Today we are just at the very beginning of making better tooling available for data science and are launching our GitHub project that will give enhanced pipelining abilities to data scientists using the PyData/R stack, with deep integration of Jupyter Notebooks. Currently Orchest supports: 1) visually and interactively editing a pipeline that is represented using a simple JSON schema; 2) running remote container based kernels through the Jupyter Enterprise Gateway integration; 3) scheduling experiments by launching parameterized pipelines on top of our Celery task scheduler; 4) configuring local and remote data sources to separate code versioning from the data passing through your pipelines. We are here to learn and get feedback from the community. As youngsters we don’t have all the answers and are always looking to improve. August 12, 2020 at 05:24AM

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Sunday, August 9, 2020

Show HN: A zsh prompt to encourage you to commit frequently https://ift.tt/30FGXl0THE RIGHT PEOPLE https://ift.tt/31wYDigTHE RIGHT PEOPLE https://ift.tt/3fJbaEi https://ift.tt/3fJbaEi

Show HN: A zsh prompt to encourage you to commit frequently https://ift.tt/3ioiVB4 August 8, 2020 at 10:07PM

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Wednesday, August 5, 2020

Launch HN: Speedscale (YC S20) – Automatically create tests from actual traffic https://ift.tt/2Po7pcJTHE RIGHT PEOPLE https://ift.tt/31m5zhRTHE RIGHT PEOPLE https://ift.tt/33rSrdS https://ift.tt/33rSrdS

Launch HN: Speedscale (YC S20) – Automatically create tests from actual traffic We’re Ken, Nate and Matt, co-founders of Speedscale ( https://speedscale.com ), a tool that automatically generates continuous integration (CI) tests from past traffic. Carefully scaling rollouts to ever larger groups of customers is the safest deployment strategy, but can take weeks. Even for elite DevOps organizations up to 15% of changes to production can result in degraded service [1] [2]. We met as undergrads at Georgia Tech and come from a DevOps and operations background so we’ve seen this first hand. Each of us has over 15 years of experience building high-reliability systems, starting in the early days with satellite earth station monitoring. As interns we once wrote a bug that caused a 32 meter antenna to try to point down through the earth, almost flattening the building we were in. It was a great environment to learn about engineering reliability. We leveraged this experience to tackle monitoring Java app servers, SOA, SaaS observability and cloud data warehouses. What if we could use a form of observability data to automatically test the reliability of new deployments before they hit production? That’s the idea that got us started on Speedscale. Most test automation tools record browser interactions or use AI to generate a set of UI tests. Speedscale works differently in that it captures API calls at the source using a Kubernetes sidecar [3] or a reverse proxy. We can see all the traffic going in and out of each service, not just the UI. We feed the traffic through an analyzer process that detects calls to external services and emulates a realistic request and response — even authentication systems like OAUTH =). Unlike guessing how users call your service, Speedscale automation reflects reality because we collected data from your live system. We call each interaction model a Scenario and Speedscale generates them without human effort leading to an easily maintained full-coverage CI test suite. Scenarios can run on demand or in your build pipeline because Speedscale inserts your container into an ephemeral environment where we stress it with different performance, regression, and chaos scenarios. If it breaks, you can decide the alerting threshold. Speedscale is especially effective in ensuring compliance with subtle Service Level Objective (SLO) conditions like performance regression [4]. We’re not public yet but would be happy to give you a demo if you contact us at hello@speedscale.com. Also, we are doing alpha customer deployments to refine our feature set and protocol support – if you have this problem or have tried to solve it in the past we would love to get your feedback. Eventually we’ll end up selling the service via a subscription model but the details are still TBD. For the moment we’re mainly focused on making the product more useful and collecting feedback. Thanks! [1] https://ift.tt/2Po7iOl… [2] https://ift.tt/2XsQtpC… [3] https://ift.tt/31pKvax… [4] https://ift.tt/3gug5du… August 5, 2020 at 06:59AM

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THE RIGHT PEOPLE

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Friday, October 23, 2020

Show HN: Easiest way to create GitHub social images https://ift.tt/37y9L2KTHE RIGHT PEOPLE https://ift.tt/2Hm8FwCTHE RIGHT PEOPLE https://ift.tt/35smwt5 https://ift.tt/35smwt5

Wednesday, October 21, 2020

Monday, October 19, 2020

Show HN: Use machine learning with this desktop app based on the igel tool https://ift.tt/2IztlRNTHE RIGHT PEOPLE https://ift.tt/35asCOBTHE RIGHT PEOPLE https://ift.tt/3m5pPNH https://ift.tt/3m5pPNHTHE RIGHT PEOPLE https://ift.tt/3kp3z0wTHE RIGHT PEOPLE https://ift.tt/3dRnHGx https://ift.tt/3dRnHGx

Show HN: Open-source portfolio and blog template built on Gatsby / Tailwind https://ift.tt/2T8GKCmTHE RIGHT PEOPLE https://ift.tt/31lh0aiTHE RIGHT PEOPLE https://ift.tt/3kfw1lu https://ift.tt/3kfw1luTHE RIGHT PEOPLE https://ift.tt/3o5fhzUTHE RIGHT PEOPLE https://ift.tt/34ddsJf https://ift.tt/34ddsJf

Thursday, October 1, 2020

Show HN: Remote scrum poker voting website (free and no login) https://ift.tt/3jqDZYUTHE RIGHT PEOPLE https://ift.tt/3l3lyttTHE RIGHT PEOPLE https://ift.tt/3cRN9Lh https://ift.tt/3cRN9Lh

Thursday, September 24, 2020

Show HN: MP3 to Text https://ift.tt/361ieecTHE RIGHT PEOPLE https://ift.tt/365JmsGTHE RIGHT PEOPLE https://ift.tt/2RVggnl https://ift.tt/2RVggnl

Thursday, September 17, 2020

Show HN: I made a website to help manage tasks with service providers https://ift.tt/2ZGYc4ETHE RIGHT PEOPLE https://ift.tt/2FPZmDGTHE RIGHT PEOPLE https://ift.tt/2ZNMbdE https://ift.tt/2ZNMbdETHE RIGHT PEOPLE https://ift.tt/32CuwaETHE RIGHT PEOPLE https://ift.tt/2E9uiyo https://ift.tt/2E9uiyo

Show HN: Tobab, a poor mans identity aware proxy. “BeyondCorp” for selfhosters https://ift.tt/3iGiCCrTHE RIGHT PEOPLE https://ift.tt/32Fk2aQTHE RIGHT PEOPLE https://ift.tt/2FIuntw https://ift.tt/2FIuntw

Show HN: Building the next-generation learning experience https://ift.tt/35Jq245THE RIGHT PEOPLE https://ift.tt/3kwZGGRTHE RIGHT PEOPLE https://ift.tt/3c96NST https://ift.tt/3c96NST