{"id":33271,"date":"2021-05-21T08:12:48","date_gmt":"2021-05-21T08:12:48","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/it5036-machine-learning-syllabus-for-it-8th-sem-2019-regulation-anna-university-professional-elective-vii\/"},"modified":"2021-05-21T08:12:48","modified_gmt":"2021-05-21T08:12:48","slug":"it5036-machine-learning-syllabus-for-it-8th-sem-2019-regulation-anna-university-professional-elective-vii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/it5036-machine-learning-syllabus-for-it-8th-sem-2019-regulation-anna-university-professional-elective-vii\/","title":{"rendered":"IT5036: Machine Learning Syllabus for IT 8th Sem 2019 Regulation Anna University (Professional Elective-VII)"},"content":{"rendered":"

Machine Learning detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the IT students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Information Technology 8th Sem scheme and its subjects, do visit IT 8th Sem 2019 regulation scheme<\/a>. For Professional Elective-VII scheme and its subjects refer to IT Professional Elective-VII syllabus scheme<\/a>. The detailed syllabus of machine learning is as follows. <\/p>\n

Machine Learning<\/title><\/p>\n<h4>Course Objective:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit II<\/h4>\n<p align=\"justify\">\n <strong>Introduction<\/strong><br \/>\n Machine Learning – Types of Machine Learning – Supervised Learning – Unsupervised Learning – Basic Concepts in Machine Learning – Machine Learning Process – Weight Space – Testing Machine Learning Algorithms – A Brief Review of Probability Theory -Turning Data into Probabilities – The Bias-Variance Tradeoff.<\/p>\n<p><i>Suggested Activities:<\/i>\n <\/p>\n<ul>\n<li>Flipped classroom on Artificial Intelligence and Expert Systems.<\/li>\n<li>Practical – Installing Python and exploring the packages required for machine learning including numpy, scikit-learn, and matplotlib, IPython hmmpytk and pgmpy.<\/li>\n<\/ul>\n<p><i>Suggested Evaluation Methods:<\/i>\n <\/p>\n<ul>\n<li>Assignments on different types of learnings.<\/li>\n<li>Tutorials on probability theory.<\/li>\n<\/ul>\n<h4>Unit II<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit III<\/h4>\n<p align=\"justify\">\n <strong>Unsupervised Learning<\/strong><br \/>\n Mixture Models and EM – K-Means Clustering – Dirichlet Process Mixture Models – Spectral Clustering – Hierarchical Clustering – The Curse of Dimensionality – Dimensionality Reduction – Principal Component Analysis – Latent Variable Models(LVM) – Latent Dirichlet Allocation (LDA).<\/p>\n<p><i>Suggested Activities:<\/i>\n <\/p>\n<ul>\n<li>Flipped classroom on mixture models.<\/li>\n<li>External learning – Improving performance of the model using kernel methods.<\/li>\n<\/ul>\n<p><i>Suggested Evaluation Methods:<\/i>\n <\/p>\n<ul>\n<li>Assignments on mixture models.<\/li>\n<\/ul>\n<h4>Unit IV<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Unit V<\/h4>\n<p align=\"justify\">\n <strong>Advanced Learning<\/strong><br \/>\n Reinforcement Learning – Representation Learning – Neural Networks – Active Learning -Ensemble Learning – Bootstrap Aggregation – Boosting – Gradient Boosting Machines -Deep Learning.<\/p>\n<p><i>Suggested Activities:<\/i>\n <\/p>\n<ul>\n<li>Flipped classroom on neural networks.<\/li>\n<li>Practical – Implement bagging approach for credit card analysis.<\/li>\n<li>External learning – Deep networks.<\/li>\n<\/ul>\n<p><i>Suggested Evaluation Methods:<\/i>\n <\/p>\n<ul>\n<li>Evaluation of the practical implementation.<\/li>\n<li>Assignments on deep networks.<\/li>\n<\/ul>\n<h4>Course Outcome:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px\"><\/a>. <\/p>\n<h4>Text Books:<\/h4>\n<p align=\"justify\">\n<ol>\n<li>Ethem Alpaydin, “Introduction to Machine Learning”, Third Edition, Prentice Hall of India, 2015.<\/li>\n<\/ol>\n<h4>References:<\/h4>\n<p align=\"justify\">\n<ol>\n<li>Christopher Bishop, “Pattern Recognition and Machine Learning”, Springer, 2006.<\/li>\n<li>Kevin P. Murphy, “Machine Learning: A Probabilistic Perspective”, MIT Press, 2012.<\/li>\n<li>Stephen Marsland, “Machine Learning – An Algorithmic Perspective”, Second Edition, CRC Press, 2014.<\/li>\n<li>Tom Mitchell, “Machine Learning”, McGraw-Hill, 2017.<\/li>\n<li>Trevor Hastie, Robert Tibshirani, Jerome Friedman, “The Elements of Statistical Learning”, Second Edition, Springer, 2008.<\/li>\n<li>Fabio Nelli, “Python Data Analytics with Pandas, Numpy, and Matplotlib”, Second Edition, Apress, 2018.<\/li>\n<\/ol>\n<p align=\"justify\">For detailed syllabus of all the other subjects of Information Technology 8th Sem, visit <a class=\"rank-math-link\" href=\"..\/category\/it+8th-sem\">IT 8th Sem subject syllabuses for 2019 regulation<\/a>. <\/p>\n<p align=\"justify\">For all Information Technology results, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-results\/\">Anna University IT all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine Learning detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the IT students. For course code, […]<\/p>\n","protected":false},"author":2297,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[72],"tags":[],"class_list":["post-33271","post","type-post","status-publish","format-standard","hentry","category-it"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/33271","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/users\/2297"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=33271"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/33271\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=33271"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=33271"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=33271"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}