Prerequisite : NA
Taught by : Plaban Kumar Bhowmik, Jiaul Hoque Paik, Mahesh Mohan M R
Teaching Assistents :
Rajkrishan Ghosh; Trishita Mukherjee; Sista Raviteja; Soumyadipta Banerjee
Supervised Learning: K-nearest Neighbor, Linear and Logistic Regression, Neural Networks, Naive Bayes, Decision Tree, Random Forest, Bagging, Adaboost, Perceptron and Support Vector Machine
Unsupervised Learning: K-means, agglomerative and hierarchical clustering, Spectral clustering, Gaussian Mixture Model
Other topics: semi-supervised learning, dimensionality reduction, Bayesian Network
Lab: Implementation of the above concepts on different datasets