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Optimization I

Difficulty level
Advanced
Speaker
Duration
1:29:05

This lecture covers the concepts of gradient descent, stochastic gradient descent, and momentum. It is a part of the Deep Learning Course at NYU's Center for Data Science. Prerequisites for this module include: Models 1-7 of this course and an Introduction to Data Science or a Graduate Level Machine Learning course.

Topics covered in this lesson

Chapters:

0:01:28 – Gradient Descent
0:14:58 – Stochastic Gradient Descent
0:27:52 – Momentum
0:44:35 – Adaptive Methods
1:05:07 – Normalization Layers
1:20:17 – The Death of Optimization

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