Python for Deep Learning - Build Neural Networks in Python - Compiling the Artificial Neural Network

The video tutorial explains the process of compiling an artificial neural network using TensorFlow. It covers the steps involved in setting up the optimizer, loss function, and evaluation metrics. The tutorial emphasizes the use of the Adam optimizer and binary cross-entropy loss function for binary classification tasks. It also highlights the importance of accuracy metrics in evaluating the model's performance.

What does the binary cross entropy function compute?

Describe how the accuracy metric is used to evaluate the neural network model.