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

The video tutorial explains the importance of the bias term in neural networks, discussing how it allows hyperplanes to not pass through the origin, which can be crucial for achieving the correct decision boundary. It also covers conventions for counting layers in neural networks, highlighting the difference between counting only hidden layers versus including the output layer. The architecture of fully connected neural networks is described, emphasizing the role of bias and connections between layers. The video concludes with a preview of the next topic: training neural networks.

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