machine-learning-book
Code Repository for Machine Learning with PyTorch and Scikit-Learn (by rasbt)
nn
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠 (by lab-ml)
machine-learning-book | nn | |
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2 | 26 | |
2,863 | 48,430 | |
- | 4.5% | |
6.8 | 7.7 | |
8 days ago | about 1 month ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
machine-learning-book
Posts with mentions or reviews of machine-learning-book.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-27.
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Implementing a ChatGPT-like LLM from scratch, step by step
Sorry, in that case I would rather recommend a dedicated RL book. The RL part in LLMs will be very specific to LLMs, and I will only cover what's absolutely relevant in terms of background info. I do have a longish intro chapter on RL in my other general ML/DL book (https://github.com/rasbt/machine-learning-book/tree/main/ch1...) but like others said, I would recommend a dedicated RL book in your case.
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"Machine Learning with PyTorch and Scikit-Learn" book
All the code examples are available here: https://github.com/rasbt/machine-learning-book
nn
Posts with mentions or reviews of nn.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-09.
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Can't remember name of website that has explanations side-by-side with code
Hey are you talking about https://nn.labml.ai/ ?
- [D] Recent ML papers to implement from scratch
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[P] GPT-NeoX inference with LLM.int8() on 24GB GPU
Implementation & LM Eval Harness Results
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[P] Fine-tuned the GPT-Neox Model to Generate Quotes
Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations/tree/master/labml_nn/neox
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Best resources to learn recent transformer papers and stay updated [D]
Regarding implementations this helps me: https://nn.labml.ai/
- Introductory papers to implement
- How to convert research papers to code?
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[D] How to convert papers to code?
Dunno if this is directly helpful, but this website has implementation with the math side by side https://nn.labml.ai/
- [D] Looking for open source projects to contribute
- Resource for papers explanation