❖ Machine learning algorithms
❖ Techniques of Machine Learning
❖ Applications of Machine Learning
❖ Review of linear algebra
❖ Data Preprocessing
❖ Supervised learning algorithms
❖ Linear Regression with single Variable
❖ Linear Regression with Multiple Variables
❖ Logistic Regression & Random Forest
❖ Decision Tree Regression
❖ Classification using KNN
❖ Classification using GINI
❖ Classification using SVM (support vector machine)
❖ Neural Networks: Representation
❖ Neural Networks: Learning for regression and classification
❖ Unsupervised learning – Clustering
❖ Mining of data using LSI
❖ Large Scale Machine Learning