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Stochastic Gradient Descent

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Overview

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This course explains stochastic gradient descent as a machine learning optimization algorithm. It covers its relationship to gradient descent, random sample selection, mini-batches, momentum, advantages and limitations, algorithmic operation, and convergence.

Syllabus

Agenda for the session.
Objective of Gradient Descent.
Gradient Descent - The Algorithm.
Types of Gradient Descent.
Stochastic Gradient Descent.
Is Stochastic Gradient Descent Same as Gradient Descent?.
Why Stochastic Gradient Descent is needed?.
How does Stochastic Gradient Descent algorithm work?.
Advantages of Gradient Descent.
Disadvantages of Stochastic Gradient Descent.
Mini batches in Gradient Descent.
Momentum in Gradient Descent.
Why does Stochastic Gradient Descent converge?.
Summarizing the session.

Taught by

Great Learning

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