For the past month, we ranked nearly 250 Machine Learning Open Source Projects to pick the Top 10.
We compared projects with new or major release during this period. Mybridge AI ranks projects based on a variety of factors to measure its quality for professionals.
Open source projects can be useful for programmers. Hope you find an interesting project that inspires you.
Dopamine: A research framework for fast prototyping of reinforcement learning algorithms — Google [5316 stars on Github]. Courtesy of Google
TransmogrifAI: An AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning [902 stars on Github]. Courtesy of Salesforce
Deep-Exemplar-based-Colorization: The source code of “Deep Exemplar-based Colorization”. [82 stars on Github]. Courtesy of MSRA CVer
YOLOv3: Training and inference in PyTorch. A state-of-the-art, real-time object detection system [353 stars on Github]. Courtesy of Ultralytics
Mantra: A high-level, rapid development framework for machine learning projects [260 stars on Github]. Courtesy of Ross Taylor
FastTSNE: Fast, parallel implementations of tSNE. A visualization of 160,796 single cell trasncriptomes from the mouse nervous system computed in exactly 2 minutes using FFT accelerated interpolation [255 stars on Github]. Courtesy of Pavlin Poličar
AIF360: An open-source library to help detect and remove bias in machine learning models. This includes metrics for datasets and models to test for biases, explanations for these metrics, and algorithms to mitigate bias in datasets and models. [159 stars on Github]. Courtesy of IBM
DeepSort: AI powered image tagger backed by DeepDetect [84 stars on Github]. Courtesy of Corentin Barreau
Zombie-Shooter-Neural-Network: Code that is used in “AI learns to shoot ZOMBIES” [4 stars on Github]. Courtesy of Daporan
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