Deep Learning with Python (Video 4)

This video tutorial introduces deep learning using the MNIST dataset of handwritten digits. It covers setting up the environment with Anaconda, Theano, and Keras, and demonstrates loading and preparing the dataset. The tutorial defines a convolutional neural network model, compiles it, and trains it using Keras. The model achieves high accuracy on the test set. The session concludes with a brief overview of the topics covered and hints at future discussions on backpropagation and Theano.

What are the steps taken to preprocess the images before feeding them into the neural network?

How does the model interpret the output as a probability over the classes?

What results were achieved after training the model, and what does this indicate?