{"id":27463,"date":"2020-07-06T05:59:35","date_gmt":"2020-07-06T05:59:35","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/machine-learning-techniques-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ-professional-elective-ii\/"},"modified":"2020-07-06T05:59:35","modified_gmt":"2020-07-06T05:59:35","slug":"machine-learning-techniques-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ-professional-elective-ii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/machine-learning-techniques-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ-professional-elective-ii\/","title":{"rendered":"Machine Learning Techniques C&amp;C 7th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective II)"},"content":{"rendered":"<p>Machine Learning Techniques C&amp;C 7th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective II) detail syllabus for Computer &amp; Communication Engineering (C&amp;C), 2017 regulation is collected from the <a href=\"https:\/\/www.annauniv.edu\/\" target=\"_blank\" rel=\"noopener\">Anna Univ<\/a> official website and presented for students of Anna University. The details of the course are: course code (CS8082), Category (PE), Contact Periods\/week (3), Teaching hours\/week (3), Practical Hours\/week (0). The total course credits are given in combined syllabus.<\/p>\n<p>For all other c&amp;c 7th sem syllabus for be 2017 regulation anna univ you can visit <a href=\"..\/cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ\">C&amp;C 7th Sem syllabus for BE 2017 regulation Anna Univ Subjects<\/a>. For all other Professional Elective II subjects do refer to <a href=\"..\/professional-elective-ii-cc-7th-sem-syllabus-for-be-2017-regulation-anna-univ\">Professional Elective II<\/a>. The detail syllabus for machine learning techniques is as follows.<\/p>\n<p><h4>Course Objective:<\/h4>\n<ul>\n<li>To understand the need for machine learning for various problem solving<\/li>\n<li>To study the various supervised, semi-supervised and unsupervised learning algorithms in<\/li>\n<p>machine learning<\/p>\n<li>To learn the new approaches in machine learning<\/li>\n<li>To design appropriate machine learning algorithms for problem solving<\/li>\n<\/ul>\n<p><h4>Unit I<\/h4>\n<p>For complete syllabus and results, class timetable and more pls <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a>. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.<\/p>\n<p><h4>Unit II<\/h4>\n<p><strong>Neural Networks and Genetic Algorithms<\/strong><br \/>\nNeural Network Representation &#8211; Problems &#8211; Perceptrons &#8211; Multilayer Networks and Back Propagation Algorithms &#8211; Advanced Topics &#8211; Genetic Algorithms &#8211; Hypothesis Space Search -Genetic Programming &#8211; Models of Evaluation and Learning.\n<\/p>\n<p><h4>Unit III<\/h4>\n<p><strong>Bayesian and Computational Learning<\/strong><br \/>\nBayes Theorem &#8211; Concept Learning &#8211; Maximum Likelihood &#8211; Minimum Description Length Principle &#8211; Bayes Optimal Classifier &#8211; Gibbs Algorithm &#8211; Naive Bayes Classifier &#8211; Bayesian Belief Network &#8211; EM Algorithm &#8211; Probability Learning &#8211; Sample Complexity &#8211; Finite and Infinite Hypothesis Spaces &#8211; Mistake Bound Model.\n<\/p>\n<p><h4>Unit IV<\/h4>\n<p>For complete syllabus and results, class timetable and more pls <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a>. Its a light weight, easy to use, no images, no pdfs platform to make students life easier.<\/p>\n<p><h4>Unit V<\/h4>\n<p><strong>Advanced Learning<\/strong><br \/>\nLearning Sets of Rules &#8211; Sequential Covering Algorithm &#8211; Learning Rule Set &#8211; First Order Rules &#8211; Sets of First Order Rules &#8211; Induction on Inverted Deduction &#8211; Inverting Resolution -Analytical Learning &#8211; Perfect Domain Theories &#8211; Explanation Base Learning &#8211; FOCL Algorithm<br \/>\n&#8211;\tReinforcement Learning &#8211; Task &#8211; Q-Learning &#8211; Temporal Difference Learning\n<\/p>\n<p><h4>Course Outcome:<\/h4>\n<p>At the end of the course, the students will be able to<\/p>\n<ul>\n<li>Differentiate between supervised, unsupervised, semi-supervised machine learning approaches<\/li>\n<li>Apply specific supervised or unsupervised machine learning algorithm for a particular problem<\/li>\n<li>Analyse and suggest the appropriate machine learning approach for the various types of problem<\/li>\n<li>Design and make modifications to existing machine learning algorithms to suit an individual application<\/li>\n<li>Provide useful case studies on the advanced machine learning algorithms<\/li>\n<\/ul>\n<p><h4>Text Books:<\/h4>\n<ol>\n<li>Tom M. Mitchell, Machine Learning, McGraw-Hill Education (India) Private Limited, 2013.<\/li>\n<\/ol>\n<p><h4>References:<\/h4>\n<ol>\n<li>Ethem Alpaydin, Introduction to Machine Learning (Adaptive Computation and<\/li>\n<p>Machine Learning), The MIT Press 2004.<\/p>\n<li>Stephen Marsland, Machine Learning: An Algorithmic Perspective, CRC Press, 2009.<\/li>\n<\/li>\n<\/ol>\n<p>For detail syllabus of all other subjects of BE C&amp;C, 2017 regulation do visit <a href=\"..\/category\/cc+7th-sem\">C&amp;C 7th Sem syllabus for 2017 Regulation<\/a>.<\/p>\n<p>Dont forget to <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">download iStudy<\/a> for latest syllabus and results, class timetable and more.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine Learning Techniques C&amp;C 7th Sem Syllabus for BE 2017 Regulation Anna Univ (Professional Elective II) detail syllabus for Computer &amp; Communication Engineering (C&amp;C), 2017 regulation is collected from the [&hellip;]<\/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":[50,68],"tags":[],"class_list":["post-27463","post","type-post","status-publish","format-standard","hentry","category-7th-sem","category-cc"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/27463","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=27463"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/27463\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=27463"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=27463"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=27463"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}