Learn basic statistics and regression for Machine Learning to know what’s going on behind the scenes. Read more.
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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.
10 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
| 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 | ||
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.
10 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
| 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 | ||
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