Lectures
The lecture presentations and the accompanying material for each lecture is posted here.
Lecture 1: Introduction
Origins of deep learning, course goals, overview of machinelearning paradigms.
Lecture 2: Multi Layer Perceptron
MLP as non linear deep model
Lecture 3: Convolution Neural Nets
This lecture is about the revolutional Convolutional neural networks
Lecture 3: Convolution Neural Nets
This lecture is about the revolutional Convolutional neural networks
Lecture 5: optimization
This lecture is about deep neural network optimization.
Lecture 6: RNN
This lecture is about recurrent neural networks.
Lecture 7: Attention
The seminal attention mechanisem
Additional Resources

From previus semesters, the videos of Alex lectures

The supplemental material page contains prerequisite topics you should be familiar with.

Detailed notes will be available for most lectures on the lecture notes page.