Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Gradient Descent Impl

The video tutorial introduces a simple neural network model using a sigmoid unit and binary cross-entropy loss function. It explains the initialization of parameters and the process of gradient descent to update these parameters. The tutorial demonstrates how the loss decreases over iterations, providing a basic understanding of gradient descent. The video concludes with a preview of more complex models and implementations in future lessons.

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