Popular AI, ML Framework & Tools


  1. Caffe
  2. Torch7
  3. Theano
  4. cuda-convnet
  5. convetjs
  6. Ccv
  7. NuPIC
  8. DeepLearning4J
  9. Brain
  10. DeepLearnToolbox
  11. Deepnet
  12. Deeppy
  13. JavaNN
  14. hebel
  15. Mocha.jl
  16. OpenDL
  17. cuDNN
  18. MGL
  19. Knet.jl
  20. Nvidia DIGITS – a web app based on Caffe
  21. Neon – Python based Deep Learning Framework
  22. Keras – Theano based Deep Learning Library
  23. Chainer – A flexible framework of neural networks for deep learning
  24. RNNLM Toolkit
  25. RNNLIB – A recurrent neural network library
  26. char-rnn
  27. MatConvNet: CNNs for MATLAB
  28. Minerva – a fast and flexible tool for deep learning on multi-GPU
  29. Brainstorm – Fast, flexible and fun neural networks.
  30. Tensorflow – Open source software library for numerical computation using data flow graphs
  31. DMTK – Microsoft Distributed Machine Learning Tookit
  32. Scikit Flow – Simplified interface for TensorFlow (mimicking Scikit Learn)
  33. MXnet – Lightweight, Portable, Flexible Distributed/Mobile Deep Learning framework
  34. Veles – Samsung Distributed machine learning platform
  35. Marvin – A Minimalist GPU-only N-Dimensional ConvNets Framework
  36. Apache SINGA – A General Distributed Deep Learning Platform
  37. DSSTNE – Amazon’s library for building Deep Learning models
  38. SyntaxNet – Google’s syntactic parser – A TensorFlow dependency library
  39. mlpack – A scalable Machine Learning library
  40. Torchnet – Torch based Deep Learning Library
  41. Paddle – PArallel Distributed Deep LEarning by Baidu
  42. NeuPy – Theano based Python library for ANN and Deep Learning
  43. Lasagne – a lightweight library to build and train neural networks in Theano
  44. nolearn – wrappers and abstractions around existing neural network libraries, most notably Lasagne
  45. Sonnet – a library for constructing neural networks by Google’s DeepMind
  46. PyTorch – Tensors and Dynamic neural networks in Python with strong GPU acceleration
  47. CNTK – Microsoft Cognitive Toolkit
  48. Serpent.AI – Game agent framework: Use any video game as a deep learning sandbox
  49. Caffe2 – A New Lightweight, Modular, and Scalable Deep Learning Framework
  50. deeplearn.js – Hardware-accelerated deep learning and linear algebra (NumPy) library for the web
  51. TVM – End to End Deep Learning Compiler Stack for CPUs, GPUs and specialized accelerators
  52. Coach – Reinforcement Learning Coach by Intel® AI Lab
  53. albumentations – A fast and framework agnostic image augmentation library
  54. Neuraxle – A general-purpose ML pipelining framework
  55. Catalyst: High-level utils for PyTorch DL & RL research. It was developed with a focus on reproducibility, fast experimentation and code/ideas reusing
  56. garage – A toolkit for reproducible reinforcement learning research
  57. Detecto – Train and run object detection models with 5-10 lines of code
  58. Karate Club – An unsupervised machine learning library for graph-structured data
  59. Synapses – A lightweight library for neural networks that runs anywhere
  60. TensorForce – A TensorFlow library for applied reinforcement learning
  61. Hopsworks – A Feature Store for ML and Data-Intensive AI
  62. Feast – A Feature Store for ML for GCP by Gojek/Google


  1. Netron – Visualizer for deep learning and machine learning models
  2. Jupyter Notebook – Web-based notebook environment for interactive computing
  3. TensorBoard – TensorFlow’s Visualization Toolkit
  4. Visual Studio Tools for AI – Develop, debug and deploy deep learning and AI solutions
  5. TensorWatch – Debugging and visualization for deep learning
  6. ML Workspace – All-in-one web-based IDE for machine learning and data science.
  7. dowel – A little logger for machine learning research. Log any object to the console, CSVs, TensorBoard, text log files, and more with just one call to logger.log()
  8. Neptune – Lightweight tool for experiment tracking and results visualization.
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