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In this blog post I share my methodology on learning machine learning in Elixir and some of the challenges I faced. I also compare the code between python and elixir. That way the reader can learn to adapt some of the code they may have seen in python over to elixir.
Trending in Blog Posts
Hey folks,
I just published a post about Hologram’s funding and where the project goes next - the short version:
Curiosum as Main Spons...
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Hi all,
In this article, I make the case for each test owning its setup.
Usually I forbid my AI agents to use the setup callbacks; I mu...
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I am seeing a lot of aplications of Argumentum ad Vericundiam in software discussions. They do link some piece of writing and point us to...
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As I’ve leaned into AI code generation on LocalCents, the volume I ship has climbed, and my worry shifted from any single change to the l...
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I recently figured out how to the the Rust hotpath profiling crate running in an elixir benchmark script (for profiling NIFs). I had some...
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This article demonstrates how to build a minimal stateful process using only Elixir’s core concurrency primitives: spawn/1, send/2, recei...
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A while back, I had to process millions of database updates in a legacy system that was already hitting its 64 GB RAM limit, so scaling t...
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Hey, I’m Jesse and I’m the main contributor behind Dexter, a full-featured, lightning-fast Elixir LSP optimized for large codebases. It s...
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Beam Bots (or just BB for short) is a framework for building fault-tolerant robotics applications in Elixir using familiar OTP patterns. ...
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Hello everyone. After busy few months I am happy to announce v0.1.0 of Emerge & Solve.
They are GUI (Emerge) and State management (S...
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There has been a thread to discuss the Stack Overflow Developer Survey on this forum every year since 2018, so here’s yet another one for...
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