There are 3,920 repositories under data-science topic.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Deep Learning for humans
scikit-learn: machine learning in Python
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.
Roadmap to becoming an Artificial Intelligence Expert in 2022
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
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 ;)
10 Weeks, 20 Lessons, Data Science for All!
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
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.
matplotlib: plotting with Python
Best Practices on Recommendation Systems
VIP cheatsheets for Stanford's CS 229 Machine Learning
500 AI Machine learning Deep learning Computer vision NLP Projects with code
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
📺 Discover the latest machine learning / AI courses on YouTube.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.