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Top Neural Network APIs for Python: TensorFlow, PyTorch, Keras, and More

Some popular neural network APIs for Python:

1. TensorFlow:

2. PyTorch:

  • Website:
  • PyTorch is an open-source deep learning library developed by Facebook’s AI Research lab (FAIR). It is known for its dynamic computational graph, making it more intuitive for many researchers.

3. Keras:

  • Website:
  • Originally an independent library, Keras has been integrated into TensorFlow. It provides a high-level neural networks API that is user-friendly and can run on top of other deep learning libraries.

4. MXNet:

  • Website:
  • MXNet is an open-source deep learning framework that is designed for both efficiency and flexibility. It is supported by the Apache Software Foundation.

5. Theano:

6. Chainer:

  • Website:
  • Chainer is a flexible and intuitive deep learning framework that allows dynamic computation graphs. It is designed to be intuitive and easy to use.

7. CNTK (Microsoft Cognitive Toolkit):

  • Website:
  • CNTK is a deep learning toolkit developed by Microsoft. It provides efficient implementations for training deep learning models.

8. Torch:

  • Website:
  • Torch is a scientific computing framework with wide support for machine learning algorithms. It has a Lua scripting language, but there is also a Python wrapper called torch7.

9. fastai:

  • Website:
  • fastai is a high-level library built on top of PyTorch. It is designed to make deep learning more accessible by providing easy-to-use APIs and pre-built models.

10. Caffe: