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?

What role does PyTorch play in automatic differentiation?