ENCS5341 | MACHINE LEARNING AND DATA SCIENCE

Data Science Life Cycle, Exploratory Data Analysis, Data Visualization, Data Preprocessing, Dimensionality Reduction and Feature Selection, Linear and polynomial Regression, Overfitting and Regularization, Logistic Regression, Neural networks, K-Nearest Neighbours, Linear Discernment Analysis, Support Vector Machines, Ensembles Methods, Bayesian Networks, Hidden Markov Model, Model Selection and Assessments, Cluster Analysis, K-Means, Hierarchal Clustering, EM and Mixture Models – EM-GMM, Cluster Validation Methods, Reinforcement learning.