COURSE SUMMARY
Course Title: 
Machine Learning and Data Mining
Course Code: 
15CSE401
Year Taught: 
2015
2016
2017
2018
Semester: 
7
Type: 
Subject Core
Degree: 
Undergraduate (UG)
School: 
School of Engineering
Campus: 
Bengaluru
Chennai
Coimbatore
Amritapuri

'Machine Learning and Data Mining' is a course offered in the seventh semester of B. Tech. in Computer Science and Engineering program at School of Engineering, Amrita Vishwa Vidyapeetham.

Unit 1

Introduction to Machine learning: Supervised learning, Unsupervised learning, some basic concepts in machine learning, Review of probability, Computational Learning theory. Bayesian concept learning, Likelihood, Posterior predictive distribution, Naive Bayes classi?ers, The log-sum-exp trick, Feature selection using mutual information, Linear Regression, Logistic regression.

Unit 2

Introduction to data mining - challenges and tasks, measures of similarity and dissimilarity, Classification - Rule based classifier, Nearest - neighbour classifiers -Bayesian classifiers - decision trees; support vector machines, Class imbalance problem performance evaluation of the classifier, comparison of different classifiers.

Unit 3

Association analysis – frequent item generation rule generation, evaluation of association patterns. Cluster analysis, K means algorithm, cluster evaluation, application of data mining to web mining and Bioinformatics. Classifying documents using bag of words advertising on the Web, Recommendation Systems, and Mining Social network graphs.

  • Kevin P. Murphey, “Machine Learning, a probabilistic perspective”, The MIT Press, 2012.
  • Jiawei Han and MichelineKamber, Jian Pei, “Data Mining: Concepts and Techniques”, Third Edition, Elsevier, 2012.
  • Pang-Ning Tan, Michael Steinbach and Vipin Kumar, “Introduction to Data Mining”, First Edition, Pearson Education, 2006.
  • Tom Mitchael, “Machine Learning”, McGraw Hill, 1997