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MIT 6.S191 (2020): Introduction to Deep Learning

MIT Introduction to Deep Learning 6.S191: Lecture 1
Foundations of Deep Learning
Lecturer: Alexander Amini
January 2020

For all lectures, slides, and lab materials: http://introtodeeplearning.com

Lecture Outline
0:00 – Introduction
4:14 – Course information
8:10 – Why deep learning?
11:01 – The perceptron
13:07 – Activation functions
15:32 – Perceptron example
18:54 – From perceptrons to neural networks
25:23 – Applying neural networks
28:16 – Loss functions
31:14 – Training and gradient descent
35:13 – Backpropagation
39:25 – Setting the learning rate
43:43 – Batched gradient descent
46:46 – Regularization: dropout and early stopping
51:58 – Summary

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