MIT Introduction to Deep Learning
Alexander Amini and Massachusetts Institute of Technology via YouTube
Overview
Syllabus
​ - Introduction
​ - Course information
​ - Why deep learning?
​ - The perceptron
​ - Activation functions
​ - Perceptron example
​ - From perceptrons to neural networks
​ - Applying neural networks
​ - Loss functions
​ - Training and gradient descent
​ - Backpropagation
​ - Setting the learning rate
​ - Batched gradient descent
​ - Regularization: dropout and early stopping
​ - Summary
Taught by
https://www.youtube.com/@AAmini/videos