Machine Leaning Class Lectures Outline Introduction to Machine Learning Supervised Learning Classification, KNN Decision Trees Classification Performance Metrics Bayes classifiers Support Vector Machine – Regression Dimensionality Reduction/ Feature Selection Cluster Analysis (K-Means) Hierarchical Clustering Association Rule Mining Ensemble Learning Wrap-Up (Recap) Notes Code and supplementary data from lectures will be shared here You can use any IDE of your choice, however jupyter is recommended for this course