There are 3,957 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.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
Roadmap to becoming an Artificial Intelligence Expert in 2022
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
10 Weeks, 20 Lessons, Data Science for All!
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 ;)
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
:memo: An awesome Data Science repository to learn and apply for real world problems.
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.
matplotlib: plotting with Python
Best Practices on Recommendation Systems
500 AI Machine learning Deep learning Computer vision NLP Projects with code
VIP cheatsheets for Stanford's CS 229 Machine Learning
🏆 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.