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All Algorithms implemented in Python
Python Data Science Handbook: full text in Jupyter Notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
Data Apps & Dashboards for Python. No JavaScript Required.
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Google's Engineering Practices documentation
List of Data Science Cheatsheets to rule the world
Companion webpage to the book "Mathematics For Machine Learning"
Code for the book Grokking Algorithms (https://www.amazon.com/dp/1633438538)
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Kepler.gl is a powerful open source geospatial analysis tool for large-scale data sets.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
Bayesian Modeling and Probabilistic Programming in Python
code for Data Science From Scratch book
A collection of machine learning examples and tutorials.
A library for setting up Ruby objects as test data.
Approaching (Almost) Any Machine Learning Problem
Code samples used on cloud.google.com
Minimal PyTorch implementation of YOLOv3
The "Python Machine Learning (2nd edition)" book code repository and info resource
A Keras implementation of YOLOv3 (Tensorflow backend)
Visually explore, understand, and present your data.
Python code for "Probabilistic Machine learning" book by Kevin Murphy