Introduction to Supervised Machine Learning and Linear Regression-Course Introduction
Welcome/Introduction Video
()
Course Prerequisites
Introduction to Supervised Machine Learning and Linear Regression-Introduction to Supervised Machine Learning
Introduction to Supervised Machine Learning: What is Machine Learning?
()
Introduction to Supervised Machine Learning: Types of Machine Learning
()
Supervised Machine Learning for Interpretation and Prediction
()
Regression and Classification Examples
()
Introduction to Supervised Machine Learning and Linear Regression-Linear Regression
Introduction to Linear Regression
()
Linear Regression Demo (Activity)
Linear Regression Demo - Part1
()
Linear Regression Demo - Part2
()
Linear Regression Demo - Part3
()
Introduction to Supervised Machine Learning and Linear Regression-End of module review & evaluation
Summary/Review
Data Splits and Cross Validation-Training and Test Splits
Training and Test Splits
()
Training and Test Splits Demo
Training and Test Splits Lab - Part 1
()
Training and Test Splits Lab - Part 2
()
Training and Test Splits Lab - Part 3
()
Training and Test Splits Lab - Part 4
()
Data Splits and Cross Validation-Cross Validation
Cross Validation
()
Cross Validation Demo
Cross Validation Demo - Part 1
()
Cross Validation Demo - Part 2
()
Cross Validation Demo - Part 3
()
Cross Validation Demo - Part 4
()
Cross Validation Demo - Part 5
()
Data Splits and Cross Validation-Polynomial Regression
Polynomial Regression
()
Data Splits and Cross Validation-End of module review & evaluation
Summary/Review
Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net-Regularization Techniques
Bias Variance Trade off
()
Regularization and Model Selection
()
Ridge Regression
()
LASSO Regression
()
Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net-Polynomial Features and Regularization Demo
Polynomial Features and Regularization Demo
Polynomial Features and Regularization Demo - Part 1
()
Polynomial Features and Regularization Demo - Part 2
()
Polynomial Features and Regularization Demo - Part 3
()
Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net-Details of Regularization
Further details of regularization
()
Details of Regularization Demo
Details of Regularization - Part 1
()
Details of Regularization - Part 2
()
Details of Regularization - Part 3
()
Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net-End of module review & evaluation
Summary/Review