Introduction To Applied Probability

Introduction To Applied Probability

HOW INTRODUCTION TO APPLIED PROBABILITY IS SET UP TO MAKE COMPLICATED PROBABILITY AND STATISTICS EASY

This course deals with concepts required for the study of Machine Learning and Data Science. Statistics is a branch of science that is an outgrowth of the Theory of Probability. Probability & Statistics are used in Machine Learning, Data Science, Computer Science and Electrical Engineering.

This 35+ lecture course includes video explanations of everything from Fundamental of Probability, and it includes more than 35+ examples (with detailed solutions) to help you test your understanding along the way. Introduction To Applied Probability is organized into the following sections:

• Introduction

• Some Basic Definitions

• Mathematical Definition of Probability

• Some Important Symbols

• Important Results

• Conditional Probability

• Theorem of Total Probability

• Baye's Theorem

• Bernoulli's Trials

• Uncountable Uniform Spaces

Fundamental Course in Probability for Machine Learning, Data Science, Computer Science and Electrical Engineering

Url: View Details

What you will learn

• Basic Definitions related to Probability Theory
• Mathematical Definition of Probability
• Important Symbols and Results related to Probability Theory

Rating: 3.8

Level: All Levels

Duration: 4 hours

Instructor: Shilank Singh