skorch
machine-learning-book
| skorch | machine-learning-book | |
|---|---|---|
| 3 | 2 | |
| 5,639 | 2,878 | |
| 0.8% | - | |
| 6.9 | 6.8 | |
| 14 days ago | 10 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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skorch
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[P] skorch 0.12.0 - HuggingFace integrations for sklearn, M1 support and others
Find a detailled list of changes in the release text.
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[P] ray-skorch - distributed PyTorch on Ray with sklearn API
I'm the principal author of ray-skorch, a library that lets you run distributed PyTorch training on large-scale datasets while providing a familiar, scikit-learn compatible skorch API, integrating well with the rest of the scikit-learn ecosystem.
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Scikit-Learn Version 1.0
There are scikit-learn (sklearn) API-compatible wrappers for e.g. PyTorch and TensorFlow.
Skorch: https://github.com/skorch-dev/skorch
tf.keras.wrappers.scikit_learn: https://www.tensorflow.org/api_docs/python/tf/keras/wrappers...
machine-learning-book
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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
What are some alternatives?
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
python-machine-learning-book-3rd-edition - The "Python Machine Learning (3rd edition)" book code repository
scikit-learn - scikit-learn: machine learning in Python
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
embedding-encoder - Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
sktime - A unified framework for machine learning with time series
gdrl - Grokking Deep Reinforcement Learning
ray-skorch - Distributed skorch on Ray Train
hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
DataFrame - C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage
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, ... 🧠