Prerequisite : None
Taught by : Adway Mitra, Plaban Bhowmik
Teaching Assistents :
Deepayan Chakraborty, Atif Hassan, Shiva Agarwal, Anjali Raj, Priyanka
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