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

The video introduces the concepts of neurons, bias, and activation functions in neural networks. It explains how neurons are connected to form a network and the role of hyperparameters in training. The structure of deep neural networks is explored, focusing on fully connected and feedforward networks. The video concludes with a discussion on implementing these concepts and hints at future topics like activation functions and bias terms.

What new insight or understanding did you gain from this video?

Evaluate responses using AI:

OFF