Data Science and Machine Learning (Theory and Projects) A to Z - Vanishing Gradients in RNN: Introduction Vanishing Grad

The video discusses the vanishing gradient problem, particularly in recurrent neural networks (RNNs), and its impact on long-term dependencies. It explains how the depth of RNNs, determined by the number of time steps, exacerbates this issue. The video also introduces the exploding gradient problem and its solution, gradient clipping. Finally, it outlines solutions to the vanishing gradient problem, including gated recurrent units (GRUs) and long short-term memory (LSTM) models.

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