MIT Introduction to Deep Learning | 6.S191
MIT Introduction to Deep Studying 6.S191: Lecture 1
*New 2023 Version*
Foundations of Deep Studying
Lecturer: Alexander Amini
For all lectures, slides, and lab supplies: http://introtodeeplearning.com/
Lecture Define
0:00 – Introduction
8:14 – Course info
11:33 – Why deep studying?
14:48 – The perceptron
20:06 – Perceptron instance
23:14 – From perceptrons to neural networks
29:34 – Making use of neural networks
32:29 – Loss capabilities
35:12 – Coaching and gradient descent
40:25 – Backpropagation
44:05 – Setting the training price
48:09 – Batched gradient descent
51:25 – Regularization: dropout and early stopping
57:16 – Abstract
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