scikit-learn: machine learning in Python

Deep Learning for humans

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Apache Superset is a Data Visualization and Data Exploration Platform

The fastai book, published as 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, AWS, and various command lines.

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 ;)

matplotlib: plotting with Python

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

A collection of machine learning examples and tutorials.

Learn how to design, develop, deploy and iterate on production-grade ML applications.

📝 An awesome Data Science repository to learn and apply for real world problems.

10 Weeks, 20 Lessons, Data Science for All!

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Open Machine Learning Course

500 AI Machine learning Deep learning Computer vision NLP Projects with code

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.