{"id":1029,"date":"2023-02-05T10:12:39","date_gmt":"2023-02-05T10:12:39","guid":{"rendered":"https:\/\/www.inspirenignite.com\/ts\/machine-learning-syllabus-for-mca-2nd-year-1st-sem-r22-regulation-jntuh\/"},"modified":"2023-02-05T10:12:39","modified_gmt":"2023-02-05T10:12:39","slug":"machine-learning-syllabus-for-mca-2nd-year-1st-sem-r22-regulation-jntuh","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/ts\/machine-learning-syllabus-for-mca-2nd-year-1st-sem-r22-regulation-jntuh\/","title":{"rendered":"Machine Learning syllabus for MCA 2nd Year 1st Sem R22 regulation JNTUH"},"content":{"rendered":"<p align=\"justify\">Machine Learning detailed syllabus for Master of Computer Applications(MCA), R22 regulation has been taken from the <a href=\"https:\/\/jntuh.ac.in\/syllabus\/\" style=\"color: inherit\" rel=\"nofollow noopener\" target=\"_blank\">JNTUH<\/a> official website and presented for the students affiliated to JNTUH course structure. For Course Code, Subject Names, Theory Lectures, Tutorial, Practical\/Drawing, Credits, and other information do visit full semester subjects post given below. The syllabus PDF files can also be downloaded from the universities official website.<\/p>\n<p align=\"justify\">For all other MCA 2nd Year 1st Sem syllabus for R22 regulation JNTUH, do visit <a href=\"..\/mca-2nd-year-1st-sem-syllabus-for-r22-regulation-jntuh\">MCA 2nd Year 1st Sem syllabus for R22 regulation JNTUH <\/a>subjects. The detailed syllabus for machine learning is as follows.  <\/p>\n<h4>Course Objectives:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" rel=\"nofollow noopener\" target=\"_blank\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students&#8217;s lives easier.<\/b><br \/><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&amp;pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" rel=\"nofollow noopener\" target=\"_blank\"><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>Course Outcomes:<\/h4>\n<p>  Upon completion of the course, the students will be able to:<\/p>\n<ul>\n<li>Distinguish between, supervised, unsupervised and semi-supervised learning<\/li>\n<li>Apply the apt machine learning strategy for any given problem<\/li>\n<li>Suggest supervised, unsupervised or semi-supervised learning algorithms for any given problem<\/li>\n<li>Design systems that use the appropriate graph models of machine learning<\/li>\n<li>Modify existing machine learning algorithms to improve classification efficiency<\/li>\n<\/ul>\n<h4>Unit I<\/h4>\n<h4>Introduction:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" rel=\"nofollow noopener\" target=\"_blank\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students&#8217;s lives easier.<\/b><br \/><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&amp;pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" rel=\"nofollow noopener\" target=\"_blank\"><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>  Linear Models: Multi-layer Perceptron- Going Forwards &#8211; Going Backwards: Back Propagation Error &#8211; Multi-layer Perceptron in Practice &#8211; Examples of using the MLP &#8211; Overview &#8211; Deriving Back-Propagation &#8211; Radial Basis Functions and Splines &#8211; Concepts &#8211; RBF Network &#8211; Curse of Dimensionality &#8211; Interpolations and Basis Functions &#8211; Support Vector Machines<\/p>\n<h4>Unit III<\/h4>\n<p>  Tree and Probabilistic Models: Learning with Trees &#8211; Decision Trees &#8211; Constructing Decision Trees &#8211; Classification and Regression Trees &#8211; Ensemble Learning &#8211; Boosting &#8211; Bagging &#8211; Different ways to Combine Classifiers &#8211; Basic Statistics -Gaussian Mixture Models &#8211; Nearest Neighbor Methods &#8211; Unsupervised Learning &#8211; K means Algorithms<\/p>\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 href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" rel=\"nofollow noopener\" target=\"_blank\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students&#8217;s lives easier.<\/b><br \/><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&amp;pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" rel=\"nofollow noopener\" target=\"_blank\"><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>  Graphical Models: Markov Chain Monte Carlo Methods &#8211; Sampling &#8211; Proposal Distribution &#8211; Markov Chain Monte Carlo -Graphical Models &#8211; Bayesian Networks &#8211; Markov Random Fields &#8211; Hidden Markov Models &#8211; Tracking Methods<\/p>\n<h4>Text Books:<\/h4>\n<ol>\n<li>Stephen Marsland, &#8216;Machine Learning &#8211; An Algorithmic Perspective, Second Edition, Chapman and Hall\/ CRC Machine Learning and Pattern Recognition Series, 2014.<\/li>\n<li>Tom M Mitchell, &#8216;Machine Learning, First Edition, McGraw Hill Education, 2013.<\/li>\n<\/ol>\n<h4>Reference Books:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete Syllabus, results, class timetable, and many other features kindly download the <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" rel=\"nofollow noopener\" target=\"_blank\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students&#8217;s lives easier.<\/b><br \/><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&amp;pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" rel=\"nofollow noopener\" target=\"_blank\"><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<p align=\"justify\">For detail syllabus of all other subjects of Master of Computer Applications 2nd Year, visit <a href=\"..\/category\/mca+2nd-year\">MCA 2nd Year syllabus<\/a> subjects.<\/p>\n<p align=\"justify\">For all MCA results, visit <a href=\"https:\/\/www.inspirenignite.com\/ts\/category\/results\/\">JNTUH MCA all years, and semester results <\/a>from direct links.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine Learning detailed syllabus for Master of Computer Applications(MCA), R22 regulation has been taken from the JNTUH official website and presented for the students affiliated to JNTUH course structure. For [&hellip;]<\/p>\n","protected":false},"author":2344,"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":[6,35],"tags":[],"class_list":["post-1029","post","type-post","status-publish","format-standard","hentry","category-2nd-year","category-mca"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/posts\/1029","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/users\/2344"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/comments?post=1029"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/posts\/1029\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/media?parent=1029"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/categories?post=1029"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/ts\/wp-json\/wp\/v2\/tags?post=1029"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}