Published 9/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 204.60 MB | Duration: 0h 52m
Probability refresher for machine learning.
What you'll learn
Refresh probability fundamentals.
Use conditional probability and Bayes' rule in machine learning
Use random variables in machine learning
Use probability distribution functions in machine learning
Manipulate multiple and interdependent random variables
Understand law of large numbers
Recall the most frequently used probability distribution functions in machine learning
Requirements
Basic knowledge of probability
Basic real analysis (integration)
Description
Probability is usually a prerequisite of machine learning. However, one doesn't need to know all the concepts in probability. In this course, I have compiled together all the important probability concepts that are most frequently used in machine learning. This is the content I taught at Polytechnique Montreal as a refresher on probability for machine learning. Understanding these concepts will help you navigate through an introductory course in machine learning.This course is for you if- You have learned probability a long time ago- You want to refresh the essential topics in probability to get started with your journey in machine learning.This course is not for you if- You want to learn probability from scratch.- You want to master all the concepts in probability.Please note that I do not cover all the topics in probability. I only cover the topics that are most frequently used in the machine learning textbook. If you want to learn probability from scratch or master all the concepts, this course is not for you.In this course, we cover the following topicsProbability basicsConditional probability and Bayes' rule Random variables Expectation and Variance Multiple random variables Law of large numbers Some important distribution functions
Overview
Section 1: Basics
Lecture 1 Introduction
Lecture 2 Basics
Lecture 3 Conditional probability and Bayes' rule
Section 2: Random variables
Lecture 4 Random variables
Lecture 5 Expectation and Variance
Lecture 6 Multiple random variables
Section 3: Other good to know stuff
Lecture 7 Law of large numbers
Lecture 8 Some important distribution functions
Students who have learned probability long time ago and want to refresh it to start their journey in machine learning
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