Please ensure Javascript is enabled for purposes of website accessibility

About This Course

Who this course is for:

  • Beginners who want to learn the mathematics for Machine Learning

What you’ll learn: 

  • Python basics
  • Statistics and Regression behind Machine Learning in Python and also using Manual Calculations

Requirements: 

  • Basic computer knowledge and an interest to learn the mathematics for Machine Learning

Hello and welcome to the course Basic Statistics and Regression for Machine Learning.

You know.. there are mainly two kinds of Machine Learning enthusiasts.

The first type fantasizes about Machine Learning and Artificial Intelligence. Thinking that it’s a magical voodoo thing. Even if they are into coding, they will just import the library, use the class and its functions. And will rely on the function to do the magic in the background.

The second kind are curious people. They are interested to learn what’s actually happening behind the scenes of these functions of the class. Even though they don’t want to go deep with all those mathematical complexities, they are still interested to learn what’s going on behind the scenes at least in a shallow Layman’s perspective way.

In this course, we are focusing mainly on the second kind of learners.

That’s why this is a special kind of course. Here we discuss the basics of Machine Learning and the Mathematics of Statistical Regression which powers almost all of the Machine Learning Algorithms.

We will have exercises for regression in both manual plain mathematical calculations and then compare the results with the ones we got using ready-made Python functions.

Our Promise to You

By the end of this course, you will have learned the Mathematics of Statistical Regression which powers almost all of the Machine Learning Algorithms.

30 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today and learn more about Machine Learning and Statistical Regression.

Course Curriculum

5h 5m

Section 1 - Course Introduction And Table Of Contents
Course Introduction And Table Of Contents 00:00:00
Section 2 - Download Source Code, Datasets And Text Files From Here
Download Source Code, Datasets And Text Files From Here 00:00:00
Section 3 - Environment Setup: Preparing Your Computer
Environment Setup – Part 1 00:00:00
Environment Setup – Part 2 00:00:00
Essential Components Included In Anaconda 00:00:00
Section 4 - Python Basics
Python Basics – Assignment 00:00:00
Python Basics – Flow Control – Part 1 00:00:00
Python Basics – Flow Control – Part 2 00:00:00
Python Basics – List And Tuples 00:00:00
Python Basics – Dictionary And Functions – Part 1 00:00:00
Python Basics – Dictionary And Functions – Part 2 00:00:00
Section 5 - Numpy Basics
Numpy Basics – Part 1 00:00:00
Numpy Basics – Part 2 00:00:00
Section 6 - Matplotlib Basics
Matplotlib Basics – Part 1 00:00:00
Matplotlib Basics – Part 2 00:00:00
Section 7 - Basics Of Data For Machine Learning
Basics Of Data For Machine Learning 00:00:00
Section 8 - Central Data Tendency
Central Data Tendency – Mean 00:00:00
Central Data Tendency – Median And Mode – Part 1 00:00:00
Central Data Tendency – Median And Mode – Part 2 00:00:00
Section 9 - Variance And Standard Deviation Manual Calculation
Variance And Standard Deviation Manual Calculation – Part 1 00:00:00
Variance And Standard Deviation Manual Calculation – Part 2 00:00:00
Variance And Standard Deviation Using Python 00:00:00
Section 10 - Percentile Manual Calculation
Percentile Manual Calculation 00:00:00
Percentile Using Python 00:00:00
Section 11 - Distribution
Uniform Distribution 00:00:00
Normal Distribution – Part 1 00:00:00
Normal Distribution – Part 2 00:00:00
Section 12 - Z Score Calculation
Manual Z Score Calculation 00:00:00
Z Score Calculation Using Python 00:00:00
Section 13 - Multi Variable Dataset Scatter Plot
Multi Variable Dataset Scatter Plot 00:00:00
Section 14 - Linear Regression
Introduction To Linear Regression 00:00:00
Manually Finding Linear Regression Correlation Coefficient – Part 1 00:00:00
Manually Finding Linear Regression Correlation Coefficient – Part 2 00:00:00
Manually Finding Linear Regression Slope Equation – Part 1 00:00:00
Manually Finding Linear Regression Slope Equation – Part 2 00:00:00
Manually Predicting The Future Value Using Equation 00:00:00
Linear Regression Using Python Introduction 00:00:00
Linear Regression Using Python – Part 1 00:00:00
Linear Regression Using Python – Part 2 00:00:00
Strong And Weak Linear Regression 00:00:00
Predicting Future Value Using Linear Regression In Python 00:00:00
Section 15 - Polynomial Regression
Polynomial Regression Introduction 00:00:00
Polynomial Regression Visualization 00:00:00
Polynomial Regression Prediction And R2 Value 00:00:00
Polynomial Regression Finding SD Components 00:00:00
Polynomial Regression Manual Method Equations 00:00:00
Finding SD Components For abc 00:00:00
Finding abc 00:00:00
Polynomial Regression Equation And Prediction 00:00:00
Polynomial Regression Coefficient 00:00:00
Section 16 - Multiple Regression
Multiple Regression Introduction 00:00:00
Multiple Regression Using Python – Part 1 – Data Import As CSV 00:00:00
Multiple Regression Using Python – Part 2 – Data Visualization 00:00:00
Creating Multiple Regression Object And Prediction Using Python 00:00:00
Manual Multiple Regression – Intro And Finding Means 00:00:00
Manual Multiple Regression – Finding Components – Part 1 00:00:00
Manual Multiple Regression – Finding Components – Part 2 00:00:00
Manual Multiple Regression – Finding abc 00:00:00
Manual Multiple Regression Equation Prediction And Coefficients 00:00:00
Section 17 - Feature Scaling
Feature Scaling Introduction 00:00:00
Standardization Scaling Using Python – Part 1 00:00:00
Standardization Scaling Using Python – Part 2 00:00:00
Standardization Scaling Using Manual Calculation – Part 1 00:00:00
Standardization Scaling Using Manual Calculation – Part 2 00:00:00
Section 18 - Further Learning References And Resource Download
Further Learning References And Resource Download 00:00:00
top
Template Design © VibeThemes. All rights reserved.

Setup Menus in Admin Panel

3954196

Get LIFETIME ACCESS to ALL courses 

Enter your Name and Email for a chance to win Lifetime Access to all courses!
Promotion ends today.

3954197

Get LIFETIME ACCESS to ALL courses 

Enter your Name and Email for a chance to win Lifetime Access to all courses!
Promotion ends today.

Success! You are now entered to win lifetime access to all courses. Winners are selected at the beginning of each month. 

P.S. Look out for our exclusive sales only shown to students on our email list!