The best Hacker News stories from Show from the past day
Latest posts:
Show HN: GraphQL Client in the Terminal
Show HN: GraphQL Client in the Terminal
Show HN: GraphQL Client in the Terminal
Show HN: Plasmo – a framework for building modern Chrome extensions
Hey HN, we're excited to have people try out our framework! When we built out a Chrome extension earlier this year, we noticed that the config was too imperative. You had to constantly tell Chrome via the manifest.json file where your files were, what your permissions should be, etc.<p>So we thought it might be interesting to build a more declarative framework. When we built a proof of concept, we enjoyed working with it and decided to invest more time into making it usable and adding more features.<p>We're still pretty early in building it out, and there's a bunch more we want to add, but this feels like a good time to showcase it and hear what people think!
Show HN: Plasmo – a framework for building modern Chrome extensions
Hey HN, we're excited to have people try out our framework! When we built out a Chrome extension earlier this year, we noticed that the config was too imperative. You had to constantly tell Chrome via the manifest.json file where your files were, what your permissions should be, etc.<p>So we thought it might be interesting to build a more declarative framework. When we built a proof of concept, we enjoyed working with it and decided to invest more time into making it usable and adding more features.<p>We're still pretty early in building it out, and there's a bunch more we want to add, but this feels like a good time to showcase it and hear what people think!
Show HN: Fast Deep Reinforcement Learning Course
I worked on this applied Deep Reinforcement Learning course for the better part of 2021. I made a Datacamp course [0] before, and this served as my inspiration to make an applied Deep RL series.<p>Normally, Deep RL courses teach a lot of mathematically involved theory. You get the practical applications near the end (if at all).<p>I have tried to turn that on its head. In the top-down approach, you learn practical skills first, then go deeper later. This is much more fun.<p>This course (the first in a planned multi-part series) shows how to use the Deep Reinforcement Learning framework RLlib to solve OpenAI Gym environments. I provide a big-picture overview of RL and show how to use the tools to get the job done. This approach is similar to learning Deep Learning by building and training various deep networks using a high-level framework e.g. Keras.<p>In the next course in the series (open for pre-enrollment), we move on to solving real-world Deep RL problems using custom environments and various tricks that make the algorithms work better [1].<p>The main advantage of this sequence is that these practical skills can be picked up fast and used in real life immediately. The involved mathematical bits can be picked up later. RLlib is the industry standard, so you won't need to change tools as you progress.<p>This is the first time that I made a course on my own. I learned flip-chart drawing to illustrate the slides and notebooks. That was fun, considering how much I suck at drawing. I am using Teachable as the LMS, Latex (Beamer) for the slides, Sketchbook for illustrations, Blue Yeti for audio recording, OBS Studio for screencasting, and Filmora for video editing. The captions are first auto-generated on YouTube and then hand edited to fix errors and improve formatting. I do the majority of the production on Linux and then switch to Windows for video editing.<p>I released the course last month and the makers of RLlib got in touch to show their approval. That's the best thing to happen so far.<p>Please feel free to try it and ask any questions. I am around and will do my best to answer them.<p>[0] <a href="https://www.datacamp.com/courses/unit-testing-for-data-science-in-python" rel="nofollow">https://www.datacamp.com/courses/unit-testing-for-data-scien...</a>
[1] <a href="https://courses.dibya.online/p/realdeeprl" rel="nofollow">https://courses.dibya.online/p/realdeeprl</a>
Show HN: Fast Deep Reinforcement Learning Course
I worked on this applied Deep Reinforcement Learning course for the better part of 2021. I made a Datacamp course [0] before, and this served as my inspiration to make an applied Deep RL series.<p>Normally, Deep RL courses teach a lot of mathematically involved theory. You get the practical applications near the end (if at all).<p>I have tried to turn that on its head. In the top-down approach, you learn practical skills first, then go deeper later. This is much more fun.<p>This course (the first in a planned multi-part series) shows how to use the Deep Reinforcement Learning framework RLlib to solve OpenAI Gym environments. I provide a big-picture overview of RL and show how to use the tools to get the job done. This approach is similar to learning Deep Learning by building and training various deep networks using a high-level framework e.g. Keras.<p>In the next course in the series (open for pre-enrollment), we move on to solving real-world Deep RL problems using custom environments and various tricks that make the algorithms work better [1].<p>The main advantage of this sequence is that these practical skills can be picked up fast and used in real life immediately. The involved mathematical bits can be picked up later. RLlib is the industry standard, so you won't need to change tools as you progress.<p>This is the first time that I made a course on my own. I learned flip-chart drawing to illustrate the slides and notebooks. That was fun, considering how much I suck at drawing. I am using Teachable as the LMS, Latex (Beamer) for the slides, Sketchbook for illustrations, Blue Yeti for audio recording, OBS Studio for screencasting, and Filmora for video editing. The captions are first auto-generated on YouTube and then hand edited to fix errors and improve formatting. I do the majority of the production on Linux and then switch to Windows for video editing.<p>I released the course last month and the makers of RLlib got in touch to show their approval. That's the best thing to happen so far.<p>Please feel free to try it and ask any questions. I am around and will do my best to answer them.<p>[0] <a href="https://www.datacamp.com/courses/unit-testing-for-data-science-in-python" rel="nofollow">https://www.datacamp.com/courses/unit-testing-for-data-scien...</a>
[1] <a href="https://courses.dibya.online/p/realdeeprl" rel="nofollow">https://courses.dibya.online/p/realdeeprl</a>
Show HN: Fast Deep Reinforcement Learning Course
I worked on this applied Deep Reinforcement Learning course for the better part of 2021. I made a Datacamp course [0] before, and this served as my inspiration to make an applied Deep RL series.<p>Normally, Deep RL courses teach a lot of mathematically involved theory. You get the practical applications near the end (if at all).<p>I have tried to turn that on its head. In the top-down approach, you learn practical skills first, then go deeper later. This is much more fun.<p>This course (the first in a planned multi-part series) shows how to use the Deep Reinforcement Learning framework RLlib to solve OpenAI Gym environments. I provide a big-picture overview of RL and show how to use the tools to get the job done. This approach is similar to learning Deep Learning by building and training various deep networks using a high-level framework e.g. Keras.<p>In the next course in the series (open for pre-enrollment), we move on to solving real-world Deep RL problems using custom environments and various tricks that make the algorithms work better [1].<p>The main advantage of this sequence is that these practical skills can be picked up fast and used in real life immediately. The involved mathematical bits can be picked up later. RLlib is the industry standard, so you won't need to change tools as you progress.<p>This is the first time that I made a course on my own. I learned flip-chart drawing to illustrate the slides and notebooks. That was fun, considering how much I suck at drawing. I am using Teachable as the LMS, Latex (Beamer) for the slides, Sketchbook for illustrations, Blue Yeti for audio recording, OBS Studio for screencasting, and Filmora for video editing. The captions are first auto-generated on YouTube and then hand edited to fix errors and improve formatting. I do the majority of the production on Linux and then switch to Windows for video editing.<p>I released the course last month and the makers of RLlib got in touch to show their approval. That's the best thing to happen so far.<p>Please feel free to try it and ask any questions. I am around and will do my best to answer them.<p>[0] <a href="https://www.datacamp.com/courses/unit-testing-for-data-science-in-python" rel="nofollow">https://www.datacamp.com/courses/unit-testing-for-data-scien...</a>
[1] <a href="https://courses.dibya.online/p/realdeeprl" rel="nofollow">https://courses.dibya.online/p/realdeeprl</a>
Show HN: I restored Palm's webOS App Catalog, SDK and online help system
My pandemic project was to find, restore and organize scattered and archived remnants of Palm/HP's mobile webOS platform to help keep these delightful little devices alive.
Show HN: I restored Palm's webOS App Catalog, SDK and online help system
My pandemic project was to find, restore and organize scattered and archived remnants of Palm/HP's mobile webOS platform to help keep these delightful little devices alive.
Show HN: I restored Palm's webOS App Catalog, SDK and online help system
My pandemic project was to find, restore and organize scattered and archived remnants of Palm/HP's mobile webOS platform to help keep these delightful little devices alive.
Show HN: I restored Palm's webOS App Catalog, SDK and online help system
My pandemic project was to find, restore and organize scattered and archived remnants of Palm/HP's mobile webOS platform to help keep these delightful little devices alive.
Show HN: I restored Palm's webOS App Catalog, SDK and online help system
My pandemic project was to find, restore and organize scattered and archived remnants of Palm/HP's mobile webOS platform to help keep these delightful little devices alive.
Show HN: BrainIDE – A feature-packed Brainfuck compiler
Show HN: Common Lisp running natively over WebAssembly for the first time
A month or so ago, I ported a Common Lisp implementation (npt) to WebAssembly to make a silly blog post, because I was bored and have a lot of time on my hands to waste with things like this (I don't have a job, and because I have next to no experience, these meaningless, silly projects tend to fill what time I do have).<p>This is significant as it's the first time Common Lisp in particular has ever been hosted on it; wasm has a few poor decisions in its design that make it less-than-conducive to being a target for Common Lisp, and a lot of the more interesting implementations require an implementation to already be on the platform for bootstrapping purposes.<p>My previous attempts using other implementations haven't gone so well, despite throwing a <i>lot</i> of time at it (as an example, I have a fork of Eclipse Common Lisp, a defunct implementation from the 1990s, sitting on my disk with a few hundred lines of changes that I finally got to successfully compile and run a handful of very basic expressions, but it blows up when you try and define anything). In comparison, I was pleasantly surprised by how little I had to do, even though I did end up scrapping <i>loads</i> of lines of my own changes to npt in the process as I got a handle on how to make it work acceptably.<p>The Emscripten toolchain and I don't get along, partially because I don't like inlining ECMAScript into my C and vice-versa, so it's little more than a neat little demo right now.<p>You can load slightly more complex programs into it by hijacking the "imp" ECMAScript function every few hundred milliseconds with strings containing <i>complete forms</i> (this is essentially a batch processor, so there's no interactivity that allows it to wait while you decide what the rest of a form should be). Only one at a time, though. It's not that fancy.<p>If you mess up at all, even just a little error, it will crash. This is by design; I disabled the debugger. It's a giant hack, and the hack I eventually decided on left it impossible to have a debugging experience, with the benefit of getting to use a closer-to-unmodified npt.<p>This could be more useful, if I spent more time on it, but it's more fun if it's just a demo. I hope you enjoy the toy I made for you.<p><a href="https://en.wikipedia.org/wiki/Batch_processing" rel="nofollow">https://en.wikipedia.org/wiki/Batch_processing</a><p>If you don't know what forms are in the context of Common Lisp:<p><a href="http://www.lispworks.com/documentation/HyperSpec/Body/03_aba.htm" rel="nofollow">http://www.lispworks.com/documentation/HyperSpec/Body/03_aba...</a><p><a href="http://www.lispworks.com/documentation/HyperSpec/Body/26_glo_c.htm#compound_form" rel="nofollow">http://www.lispworks.com/documentation/HyperSpec/Body/26_glo...</a>
Show HN: I hacked my son’s Duplo train to go faster using my voice
Show HN: I hacked my son’s Duplo train to go faster using my voice
Show HN: I hacked my son’s Duplo train to go faster using my voice
Show HN: I spent my vacation writing a modern JVM assembler
Show HN: I spent my vacation writing a modern JVM assembler