Replies: 4 comments 3 replies
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Hi all, Certainly not the most prominent nor representative user of scikit-learn, I'm a CS and AI teacher using it for educational purposes. As we all know, the project is great for teaching the fundamentals of Machine Learning. However, I think its source code has become a little bit too complicated to serve as "an executable alternative to textbooks", as mentioned in Varoquaux et al., 2015. A pet project of mine is to create a "scikit-learn lite" library that would feature the bare essential algorithms and tools of ML, implemented in the clearest possible way. The goal is that its source code would be transparent enough to serve as a reference textbook. In an ideal world, I would teach ML using this white-box library instead of scikit-learn 😄. The pyfit project, still in its infancy, is my very modest attempt at fulfilling this purpose. Anyway, many thanks to all the scikit-learn maintainers and contributors for providing us with this great tool 👍. |
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For info, until yours is complete, you might start using similar projects like https://github.com/eriklindernoren/ML-From-Scratch and https://github.com/rushter/MLAlgorithms ;) |
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Thanks for your reply. I have these projects starred for a while and use them as references for my own implementation, along with other ones like https://github.com/trekhleb/homemade-machine-learning. A key difference is that I'd like to build a tiny autograd engine (inspired by https://github.com/karpathy/micrograd, https://github.com/joelgrus/autograd and the very first implementations of PyTorch) and also include type annotations. |
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Lower-level, but also related https://the-algorithms.com/ |
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Hi, my name is Robert, I'm a CS student who has had a bit of experience using sci-kit on jupyter notebook. |
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Hi, everyone |
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hello everyone , i am a computer science student and data scientist who is started with open source. |
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