Author(s): Tan Pengshi Alvin Originally published on Towards AI. A side-by-side comparison of PyTorch and TensorFlow for training and inference of neural ne ...

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PyTorch and TensorFlow are the most popular frameworks in the deep learning community, providing customizable boilerplates for coding neural network architectures and optimizing computations with GPU resources. Without these frameworks, deep learning models had to be coded from scratch using Numpy, which is more cumbersome and slower without GPU optimization. Familiarity with these frameworks enhances the development of neural networks significantly.

An Introduction to PyTorch versus TensorFlow for Deep Learning

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