Discover the Best Open-Source Data-science Projects Sorted by Stars

Deep Learning for humans

scikit-learn: machine learning in Python

Apache Superset is a Data Visualization and Data Exploration Platform

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

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

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

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

💫 Industrial-strength Natural Language Processing (NLP) in Python

Streamlit — A faster way to build and share data apps.

Roadmap to becoming an Artificial Intelligence Expert in 2022

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 ;)

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.

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Deep learning framework to train, deploy, and ship AI products Lightning fast.

10 Weeks, 20 Lessons, Data Science for All!

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.

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

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

Data Apps & Dashboards for Python. No JavaScript Required.

The fastai book, published as Jupyter Notebooks