Data Science and Machine Learning (Theory and Projects) A to Z - RNN Implementation: Automatic Differentiation
Interactive Video
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Information Technology (IT), Architecture
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University
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Practice Problem
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Hard
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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.
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2 questions
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1.
OPEN ENDED QUESTION
3 mins • 1 pt
What challenges are associated with gradient computation in large recurrent neural networks?
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2.
OPEN ENDED QUESTION
3 mins • 1 pt
What role does PyTorch play in automatic differentiation?
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