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Python Data Science Handbook: full text in Jupyter Notebooks
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Learn how to design, develop, deploy and iterate on production-grade ML applications.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
A game theoretic approach to explain the output of any machine learning model.
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
The "Python Machine Learning (1st edition)" book code repository and info resource
PRML algorithms implemented in Python
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Anthropic's educational courses
Notebooks and code for the book "Introduction to Machine Learning with Python"
Visualizations for machine learning datasets
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
From the basics to slightly more interesting applications of Tensorflow
Create delightful software with Jupyter Notebooks
The "Python Machine Learning (3rd edition)" book code repository
A collection of infrastructure and tools for research in neural network interpretability.
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
🛠 All-in-one web-based IDE specialized for machine learning and data science.
MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
