Welcome to the course!
1
Applications of Machine Learning
2
Why Machine Learning is the Future
3
Important notes, tips & tricks for this course
4
This PDF resource will help you a lot
6
Installing Python and Anaconda (Mac, Linux & Windows)
7
Update: Recommended Anaconda Version
8
Installing R and R Studio (Mac, Linux & Windows)
9
BONUS: Meet your instructors
-------------------- Part 1: Data Preprocessing --------------------
1
Welcome to Part 1 - Data Preprocessing
5
For Python learners, summary of Object-oriented programming: classes & objects
9
Splitting the Dataset into the Training set and Test set
11
And here is our Data Preprocessing Template!
-------------------- Part 2: Regression --------------------
1
Welcome to Part 2 - Regression
Simple Linear Regression
2
Dataset + Business Problem Description
3
Simple Linear Regression Intuition - Step 1
4
Simple Linear Regression Intuition - Step 2
5
Simple Linear Regression in Python - Step 1
6
Simple Linear Regression in Python - Step 2
7
Simple Linear Regression in Python - Step 3
8
Simple Linear Regression in Python - Step 4
9
Simple Linear Regression in R - Step 1
10
Simple Linear Regression in R - Step 2
11
Simple Linear Regression in R - Step 3
12
Simple Linear Regression in R - Step 4
Multiple Linear Regression
2
Dataset + Business Problem Description
3
Multiple Linear Regression Intuition - Step 1
4
Multiple Linear Regression Intuition - Step 2
5
Multiple Linear Regression Intuition - Step 3
6
Multiple Linear Regression Intuition - Step 4
7
Prerequisites: What is the P-Value?
8
Multiple Linear Regression Intuition - Step 5
9
Multiple Linear Regression in Python - Step 1
10
Multiple Linear Regression in Python - Step 2
11
Multiple Linear Regression in Python - Step 3
12
Multiple Linear Regression in Python - Backward Elimination - Preparation
13
Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !
14
Multiple Linear Regression in Python - Backward Elimination - Homework Solution
15
Multiple Linear Regression in Python - Automatic Backward Elimination
16
Multiple Linear Regression in R - Step 1
17
Multiple Linear Regression in R - Step 2
18
Multiple Linear Regression in R - Step 3
19
Multiple Linear Regression in R - Backward Elimination - HOMEWORK !
20
Multiple Linear Regression in R - Backward Elimination - Homework Solution
21
Multiple Linear Regression in R - Automatic Backward Elimination
22
Multiple Linear Regression
Polynomial Regression
1
Polynomial Regression Intuition
3
Polynomial Regression in Python - Step 1
4
Polynomial Regression in Python - Step 2
5
Polynomial Regression in Python - Step 3
6
Polynomial Regression in Python - Step 4
7
Python Regression Template
8
Polynomial Regression in R - Step 1
9
Polynomial Regression in R - Step 2
10
Polynomial Regression in R - Step 3
11
Polynomial Regression in R - Step 4
Support Vector Regression (SVR)
Decision Tree Regression
1
Decision Tree Regression Intuition
3
Decision Tree Regression in Python
4
Decision Tree Regression in R
Random Forest Regression
1
Random Forest Regression Intuition
3
Random Forest Regression in Python
4
Random Forest Regression in R
Evaluating Regression Models Performance
2
Adjusted R-Squared Intuition
3
Evaluating Regression Models Performance - Homework's Final Part
4
Interpreting Linear Regression Coefficients
5
Conclusion of Part 2 - Regression
-------------------- Part 3: Classification --------------------
1
Welcome to Part 3 - Classification
Logistic Regression
1
Logistic Regression Intuition
