Reinforcement Learning and Deep RL Python Theory and Projects - Perceptron

The video tutorial introduces deep neural networks, focusing on perceptrons, which are fundamental units in these networks. It explains the role of inputs, weights, and the importance of activation functions. The tutorial also covers how neurons are connected to form larger networks and provides a practical implementation of perceptrons in PyTorch, initially without activation functions.

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