Data Science and Machine Learning (Theory and Projects) A to Z - RNN Implementation: Automatic Differentiation

The video discusses the challenges of gradient computation in neural networks, particularly in recurrent neural networks (RNNs). It introduces automatic differentiation as a solution, highlighting its simplicity compared to analytical methods. The video also introduces PyTorch, a deep learning package from Facebook, and mentions other packages like TensorFlow and MxNet. The focus is on simplifying gradient computations using these tools, with a promise to demonstrate automatic differentiation in PyTorch in the next video.

What challenges are associated with gradient computation in large recurrent neural networks?

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What role does PyTorch play in automatic differentiation?

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