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 machine-learning 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
Lecture 8: Transformers and LLMs
Video Watch Here
Additional Resources
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From previus semesters, the videos of Alex lectures
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The supplemental material page contains prerequisite topics you should be familiar with.
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Detailed notes will be available for most lectures on the lecture notes page.