Deep Learning with Python (Video 8)

This video tutorial explores the use of Theano and Keras for training neural network models. It delves into the behind-the-scenes workings of Keras, focusing on how it defines and connects multiple layers in a model. The tutorial explains the sequential model structure in Keras, detailing the process of compiling and training models using optimizers and loss functions. It also covers the fit method, emphasizing the importance of validation data to prevent overfitting. The video concludes with an overview of how Keras automates the process of writing symbolic expressions and compiling functions.

What is the role of the optimizer in the compile method?

How does Keras handle the definition of updates in the compile method?

What are the implications of overfitting in a neural network model?