handson-ml
python-machine-learning-book-3rd-edition
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| handson-ml | python-machine-learning-book-3rd-edition | |
|---|---|---|
| 1 | 3 | |
| 25,090 | 4,386 | |
| - | - | |
| 0.0 | 0.0 | |
| 7 months ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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handson-ml
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need a book recommendation for machine learning on python
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is often recommended. You can check out the GitHub repo first: https://github.com/ageron/handson-ml
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...
What are some alternatives?
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AeroPython - Classical Aerodynamics of potential flow using Python and Jupyter Notebooks
aws-lambda-docker-serverless-inference - Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.
Machine-Learning-Specialization-Coursera - Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
embedding-encoder - Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
machine-learning-book - Code Repository for Machine Learning with PyTorch and Scikit-Learn
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.
python-machine-learning-book-3rd-ed
weightless_NN_decompression - Proof of concept for neural network decompression without storing any weights