Fundamentals of Neural Networks - Forward Propagation

The video tutorial explains the architecture of a neural network using a housing dataset. It covers the concept of fully connected layers, weights, and forward propagation. The tutorial introduces the linear combination of inputs and weights, followed by the selection of an activation function, specifically the Radu function. The Radu function is defined and graphed, showing its application in predicting housing prices. The video concludes with a discussion on forward propagation and the orientation of neural network graphs.

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