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Starred repositories
A community based Python library for quantitative economics
Visual analysis and diagnostic tools to facilitate machine learning model selection.
The "Python Machine Learning (3rd edition)" book code repository
An intuitive library to add plotting functionality to scikit-learn objects.
Time Series Analysis and Forecasting in Python
Heroku's classic buildpack for Python applications.
Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
Statsmodels: statistical modeling and econometrics in Python
The "Python Machine Learning (1st edition)" book code repository and info resource
Data Visualization With Matplotlib and Seaborn
pandas, scikit-learn, xgboost and seaborn integration
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Best Practices on Recommendation Systems
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,…
Streamlit — A faster way to build and share data apps.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
scikit-learn: machine learning in Python
Keras documentation, hosted live at keras.io
500 AI Machine learning Deep learning Computer vision NLP Projects with code
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
A curated list of awesome Machine Learning frameworks, libraries and software.
📝 An awesome Data Science repository to learn and apply for real world problems.
10 Weeks, 20 Lessons, Data Science for All!
📊 Path to a free self-taught education in Data Science!