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Top AI Frameworks & Tools

AI Frameworks and Tools

Framework

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

Tools

  1. 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()
  2. Jupyter Notebook – Web-based notebook environment for interactive computing
  3. ML Workspace – All-in-one web-based IDE for machine learning and data science.
  4. Neptune – Lightweight tool for experiment tracking and results visualization.
  5. Netron – Visualizer for deep learning and machine learning models
  6. TensorBoard – TensorFlow’s Visualization Toolkit
  7. TensorWatch – Debugging and visualization for deep learning
  8. Visual Studio Tools for AI – Develop, debug and deploy deep learning and AI solutions
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