{"id":1895,"date":"2016-07-02T14:14:17","date_gmt":"2016-07-02T14:14:17","guid":{"rendered":"http:\/\/www.inspirenignite.com\/jntuh\/?p=1895"},"modified":"2021-10-27T20:40:08","modified_gmt":"2021-10-27T20:40:08","slug":"jntuh-b-tech-4th-year-1-sem-computer-science-and-engineering-r13-4-1-machine-learning-elective-ii-r13-syllabus","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/jntuh\/jntuh-b-tech-4th-year-1-sem-computer-science-and-engineering-r13-4-1-machine-learning-elective-ii-r13-syllabus\/","title":{"rendered":"JNTUH B.Tech 4th Year 1 sem Computer Science and Engineering R13 (4-1) Machine Learning  (Elective \u2013 II) R13 syllabus."},"content":{"rendered":"<p style=\"text-align: justify\">JNTUH B.Tech 4th year (4-1) Machine Learning gives you detail information of Machine Learning (Elective \u2013 II) R13 syllabus It will be help full to understand you complete curriculum of the year.<\/p>\n<p style=\"text-align: justify\"><strong>Objectives<\/strong><\/p>\n<ul>\n<li>To be able to formulate machine learning problems corresponding to different applications.<\/li>\n<li>To understand a range of machine learning algorithms along with their strengths and weaknesses.<\/li>\n<li>To understand the basic theory underlying machine learning.<\/li>\n<\/ul>\n<p><strong>UNIT \u2014 I<\/strong><\/p>\n<p style=\"text-align: justify\"><strong>Introduction:<\/strong> An illustrative learning task, and a few approaches to it. What is known from algorithms\/ Theory, Experiment. Biology. Psychology.<\/p>\n<p style=\"text-align: justify\"><strong>Concept Learning:<\/strong> Version spaces. Inductive Bias. Active queries. Mistake bound\/ PAC model. basic results. Overview of Issues regarding data sources, success criteria.<\/p>\n<p><strong>UNIT -II<\/strong><\/p>\n<p style=\"text-align: justify\"><strong>Decision Tree Learning<\/strong>: &#8211; Minimum Description Length Principle. Occam&#8217;s razor. Learning with active queries Neural Network Learning: Perceptions and gradient descent back propagation.<\/p>\n<p><strong>UNIT \u2014III<\/strong><\/p>\n<p style=\"text-align: justify\"><strong>Sample Complexity and Over fitting:<\/strong> Errors in estimating means. Cross Validation and jackknifing VC dimension. Irrelevant features: Multiplicative rules for weight tuning. Bayesian Approaches: The basics Expectation Maximization. Hidden Markov Models.<\/p>\n<p style=\"text-align: center\"><strong><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #ff0000\">Download iStudy Android App for complete JNTUH syllabus, results, timetables and all other updates. There are no ads and no pdfs and will make your life way easier<\/span>.<\/a><\/strong><\/p>\n<p><strong>TEXT BOOKS<\/strong><\/p>\n<ul>\n<li>Tom Michel, Machine Learning. Mc Graw Hill. 1997<\/li>\n<li>Trevor Hus tie, Robert Tibshirani &amp; Jerome Friedman. The Elements of \u00a0Statically \u00a0Learning, Springer Veriag 2001<\/li>\n<\/ul>\n<p><strong>REFERENCE BOOKS<\/strong><\/p>\n<ul>\n<li>Machine Learning Methods en the Environmental Science, Neural Network, William W Hsieh Cambridge \u00a0University Press.<\/li>\n<li>Rbchard o Duda, Peter E. Hart and David G. Stork, &amp; pattern Classification,.John Wiley &amp; Sons Inc,2001<\/li>\n<li>Chris Bishop, Neural \u00a0Network for, Pattern Recognition, Oxford University Press. 1995<\/li>\n<\/ul>\n<p><strong>Outcomes<\/strong><\/p>\n<ul>\n<li>Student Should be we to understand the basic concepts such decision tree and \u00a0neural networks.<\/li>\n<li>Ability to formulate machine learning techniques to respective problems.<\/li>\n<li>Apply \u00a0machine learning \u00a0algorithms to solve problems of moderate complexity.<\/li>\n<\/ul>\n<p>For more information about all JNTU updates please stay connected to us on FB and don\u2019t hesitate to ask any questions in the comment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>JNTUH B.Tech 4th year (4-1) Machine Learning gives you detail information of Machine Learning (Elective \u2013 II) R13 syllabus It will be help full to understand you complete curriculum of [&hellip;]<\/p>\n","protected":false},"author":2259,"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":[2,152,123,62],"tags":[],"class_list":["post-1895","post","type-post","status-publish","format-standard","hentry","category-cse","category-1st-sem-2","category-4th-year","category-syllabus"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts\/1895","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/users\/2259"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/comments?post=1895"}],"version-history":[{"count":5,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts\/1895\/revisions"}],"predecessor-version":[{"id":17386,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts\/1895\/revisions\/17386"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/media?parent=1895"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/categories?post=1895"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/tags?post=1895"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}