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Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma
This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi
This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data manipulation and analysis. It serves as a tabular data processing guide and a manual for time series analysis, providing a structured approach to cleaning, merging, and transforming datasets. The repository functions as a data feature engineering course, providing tutorials on constructing and selecting dataset features to improve machine learning model performance. It also includes a vectorized data operations guide for performing element-wise mathematical computations and matrix
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
The main features of featureform/featureform are: Feature Store, Feature Engineering, Feature Stores.
Projects with overlapping indexed features include: feast-dev/feast — Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and… nyandwi/machine_learning_complete — This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep… datawhalechina/joyful-pandas — This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data… azukds/tubular — Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes. chasedehan/boostaroota — A fast xgboost feature selection algorithm. bytehub-ai/bytehub — ByteHub: making feature stores simple.