Modules & Slides

Modules

The following Modules (Chapters) are suggested for the course -

Chapter # 01 - Introduction to Machine Learning (ML) & Concepts
Chapter # 02 - Introduction to R and Python and Exploratory Data Analysis (EDA)
Chapter # 03 - KNN Algorithm and Fundamental Concepts in ML Modeling
Chapter # 04 - Logistic Regression Algorithm
Chapter # 05 - Discriminant Analysis
Chapter # 06 - Naive Bayes and Support Vector Machine (SVM)
Chapter # 07 - Linear Regression
Chapter # 08 - Decision Tree Analysis
Chapter # 09 - Dimension Reduction and Principal Component Analysis
Chapter # 10 - K- Means Clustering

The slides for the course are available here.