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What are the differences between TensorFlow and PyTorch, both in terms of performance and functionality?

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TensorFlow was developed by Google and is based on Theano (Python library), while Facebook developed PyTorch using the Torch library. Both frames are useful and have a great community behind them. Both provide machine learning libraries to accomplish various tasks and do the job. TensorFlow is a powerful and deep learning tool with active visualization and debugging capabilities. TensorFlow also offers serialization benefits since the entire graphic is saved as a protocol buffer. It also has support for mobile platforms and offers a production-ready implementation. PyTorch, on the other hand, is still gaining momentum and attracting Python developers, since it is more Python friendly. In summary, TensorFlow is used to speed things up and create AI-related products, while research-oriented developers prefer PyTorch.

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