Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Backprop

The video tutorial explains the gradient descent algorithm, focusing on its role in minimizing loss in machine learning models. It covers the concept of derivatives and gradients, essential for optimization, and describes the architecture of neural networks, including the process of backpropagation. The tutorial also discusses tools and libraries available for computing derivatives, emphasizing their importance in training neural networks efficiently.

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