BE Computer Engineering Semester 8 (BE Fourth Year)University of Mumbai
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Machine Learning Semester 8 (BE Fourth Year) BE Computer Engineering University of Mumbai Topics and Syllabus

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CBCGS [2019 - current]
CBGS [2015 - 2018]
Old [2000 - 2014]

Topics with syllabus and resources

100.00 Introduction to Machine Learning
  • What is Machine Learning?, Key Terminology, Types of Machine Learning, Issues in Machine Learning, Application of Machine Learning, How to choose the right algorithm, Steps in developing a Machine Learning Application.
200.00 Learning with Regression
  • Linear Regression, Logistic Regression.
300.00 Learning with Trees
  • Using Decision Trees, Constructing Decision Trees, Classification and Regression Trees (CART).
400.00 Support Vector Machines (SVM)
  • Maximum Margin Linear Separators, Quadratic Programming solution to finding maximum margin separators, Kernels for learning non-linear functions.
500.00 Learning with Classification
  • Rule based classification, classification by backpropoagation, Bayesian Belief networks, Hidden Markov Models.
600.00 Dimensionality Reduction
  • Dimensionality Reduction Techniques, Principal Component Analysis, Independent Component Analysis.
700.00 Learning with Clustering
  • K-means clustering, Hierarchical clustering, Expectation Maximization Algorithm, Supervised learning after clustering, Radial Basis functions.
800.00 Reinforcement Learning
  • Introduction, Elements of Reinforcement Learning, Model based learning, Temporal Difference Learning, Generalization, Partially Observable States.
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