Material Used for the TSS-2018 sessions on Machine Learning
Session 1 – Intro, Types of ML, Overview of the basics of Statistics. Pre-processing, Linear Regression and Gradient Descent, Cross Validation
Session 2 – Classification, Logistic Regression, Decision Trees, Random Forest Classification
Session 3 – Neural Networks, Softmax classifier
Session 4 – Regularisation, Bias vs Variance, Principal Component Analysis
Session 5 - Support Vector Machines, Unsupervised Learning, K-means Algorithms, Conclusion