python-machine-learning-book-3rd-edition
machine-learning-book
| python-machine-learning-book-3rd-edition | machine-learning-book | |
|---|---|---|
| 3 | 2 | |
| 4,386 | 2,878 | |
| - | - | |
| 0.0 | 6.8 | |
| about 1 year ago | 7 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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python-machine-learning-book-3rd-edition
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What does %-*s do in a print statement?
from Cell 53, here
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The Best Mode Of Learning - Switching From Electrical Engineering To Data Science
Data Science Textbooks : Learning from a textbook provides a more refined and in-depth knowledge beyond what you get from online courses. This book provides a great introduction to data science and machine learning, with code included: “Python Machine Learning”, by Sebastian Raschka. https://github.com/rasbt/python-machine-learning-book-3rd-edition
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The Programmer's Brain
Sure! I don't intend to shill so here is a link to his github repo for the book.
https://github.com/rasbt/python-machine-learning-book-3rd-ed...
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?
linear-tree - A python library to build Model Trees with Linear Models at the leaves.
skorch - A scikit-learn compatible neural network library that wraps PyTorch
aws-lambda-docker-serverless-inference - Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
handson-ml - ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
embedding-encoder - Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
gdrl - Grokking Deep Reinforcement Learning
python-machine-learning-book-3rd-ed
hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
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, ... 🧠