What you learn in Stochastic Gradient Descent ?

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Objective of Gradient Descent
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Gradient Descent Algorithm
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Stochastic Gradient Descent
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Stochastic Gradient Descent Working
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Advantages and Disadvantages of Stochastic Gradient Descent
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About this Course

Stochastic is a process involving a randomly determined sequence of observations, each of which is considered as a sample of one element from a probability distribution or, in simple terms, Random selection. In this course, you will learn about Stochastic Gradient Decent, how it works, the difference between SGD and Gradient Descent, Mini Batches, and momentum in this process.

Course Outline

Introduction and Agenda of Stochastic Gradient Descent
Objective of Gradient Descent
Gradient Descent – The Algorithm
Types of Gradient Descent
Stochastic Gradient Descent
Is Stochastic Gradient Descent same as Gradient Descent?
Why is Stochastic Gradient Descent Needed ?
How Does Stochastic Gradient Descent Algorithm Works ?
Advantages of Stochastic Gradient Descent
Disadvantages of Stochastic Gradient Descent
Mini Batches in Gradient Descent
Momentum in Gradient Descent
Why Does Stochastic Gradient Descent Converge ?
Summary of Stochastic Gradient Descent

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Stochastic Gradient Descent

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2.0 Hours

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