Gradient-Based Algorithms in High-Dimensional Learning

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Provides an overview of Machine Learning, including historical context, key tasks, and real-world applications.

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Deep Learning: Data Representations and Neural Networks

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Double Descent Curves: Overparametrization

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Deep Learning: Convolutional Neural Networks

Covers Convolutional Neural Networks, standard architectures, training techniques, and adversarial examples in deep learning.

Deep Learning: Convolutional Neural Networks

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Covers the fundamentals of multilayer neural networks and deep learning, including back-propagation and network architectures like LeNet, AlexNet, and VGG-16.

Deep Learning Fundamentals

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Convolutional Neural Networks

Covers Convolutional Neural Networks, including layers, training strategies, standard architectures, tasks like semantic segmentation, and deep learning tricks.

Supervised Learning Overview

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