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Machine Learning Open Source of the Month (v.Sep 2018)

Machine Learning Open Source of the Month (v.Sep 2018)

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.

  • Average number of Github stars in this edition: 728 ⭐️
  • “Watch” Machine Learning Top 10 Open Source on Github and get email once a month.
  • Topics: Research Framework, AutoML library, Deep Learning, PyTorch, TSNE, Algorithm Toolbox, Fairness-ai, Deepdetect, ZOMBIES

Open source projects can be useful for programmers. Hope you find an interesting project that inspires you.

Rank 1

Dopamine: A research framework for fast prototyping of reinforcement learning algorithms — Google [5316 stars on Github]. Courtesy of Google


Rank 2

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


Rank 3

Deep-Exemplar-based-Colorization: The source code of “Deep Exemplar-based Colorization”. [82 stars on Github]. Courtesy of MSRA CVer


Rank 4

YOLOv3: Training and inference in PyTorch. A state-of-the-art, real-time object detection system [353 stars on Github]. Courtesy of Ultralytics


Rank 5

Mantra: A high-level, rapid development framework for machine learning projects [260 stars on Github]. Courtesy of Ross Taylor


Rank 6

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


Rank 7

Evolute: A simple tool for quick experimentation with evolutionary algorithms for numerical optimization. [111 stars on Github]. Courtesy of Csaba Gór


Rank 8

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


Rank 9

DeepSort: AI powered image tagger backed by DeepDetect [84 stars on Github]. Courtesy of Corentin Barreau


Rank 10

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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