{"id":50614,"date":"2023-03-22T07:13:29","date_gmt":"2023-03-22T07:13:29","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/al3461-machine-learning-laboratory-syllabus-for-aids-2021-regulation\/"},"modified":"2023-03-22T07:13:29","modified_gmt":"2023-03-22T07:13:29","slug":"al3461-machine-learning-laboratory-syllabus-for-aids-2021-regulation","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/al3461-machine-learning-laboratory-syllabus-for-aids-2021-regulation\/","title":{"rendered":"AL3461: Machine Learning Laboratory syllabus for AI&amp;DS 2021 regulation"},"content":{"rendered":"<p align=\"justify\">Machine Learning Laboratory detailed syllabus for Artificial Intelligence &amp; Data Science (AI&amp;DS) for 2021 regulation curriculum has been taken from the <a class=\"rank-math-link\" href=\"https:\/\/cac.annauniv.edu\/\" style=\"color: inherit\" target=\"_blank\" rel=\"noopener\">Anna University<\/a> official website and presented for the AI&amp;DS 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<p align=\"justify\">For Artificial Intelligence &amp; Data Science 4th Sem scheme and its subjects, do visit <a class=\"rank-math-link\" href=\"..\/ai-ds-4th-sem-syllabus-2021-regulation\">AI&amp;DS 4th Sem 2021 regulation scheme<\/a>. The detailed syllabus of machine learning laboratory is as follows. <\/p>\n<p>  <title>Machine Learning Laboratory<\/title><\/p>\n<h4>Course Objectives:<\/h4>\n<ul>\n<li>To understand the data sets and apply suitable algorithms for selecting the appropriate features for analysis.<\/li>\n<li>To learn to implement supervised machine learning algorithms on standard datasets and evaluate the performance.<\/li>\n<li>To experiment the unsupervised machine learning algorithms on standard datasets and evaluate the performance.<\/li>\n<li>To build the graph based learning models for standard data sets.<\/li>\n<li>To compare the performance of different ML algorithms and select the suitable one based on the application.<\/li>\n<\/ul>\n<h4>List of Experiments:<\/h4>\n<ol>\n<li>For a given set of training data examples stored in a .CSV file, implement and demonstrate the Candidate-Elimination algorithm to output a description of the set of all hypotheses consistent with the training examples.<\/li>\n<li>Write a program to demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample.<\/li>\n<li>Build an Artificial Neural Network by implementing the Backpropagation algorithm and test the same using appropriate data sets.<\/li>\n<li>Write a program to implement the naive Bayesian classifier for a sample training data set stored as a .CSV file and compute the accuracy with a few test data sets.<\/li>\n<li>Implement naive Bayesian Classifier model to classify a set of documents and measure the accuracy, precision, and recall.<\/li>\n<li>Write a program to construct a Bayesian network to diagnose CORONA infection using standard WHO Data Set.<\/li>\n<li>Apply EM algorithm to cluster a set of data stored in a .CSV file. Use the same data set for clustering using the k-Means algorithm. Compare the results of these two algorithms.<\/li>\n<li>Write a program to implement k-Nearest Neighbour algorithm to classify the iris data set. Print both correct and wrong predictions.<\/li>\n<li>Implement the non-parametric Locally Weighted Regression algorithm in order to fit data points. Select an appropriate data set for your experiment and draw graphs.<\/li>\n<\/ol>\n<h4>List of Equipments:(30 Students Per Batch)<\/h4>\n<p>  The programs can be implemented in either Python or R.<\/p>\n<h4>Course Outcomes:<\/h4>\n<p>  At the end of this course, the students will be able to:<\/p>\n<ol>\n<li>Apply suitable algorithms for selecting the appropriate features for analysis.<\/li>\n<li>Implement supervised machine learning algorithms on standard datasets and evaluate the performance.<\/li>\n<li>Apply unsupervised machine learning algorithms on standard datasets and evaluate the performance.<\/li>\n<li>Build the graph based learning models for standard data sets.<\/li>\n<li>Assess and compare the performance of different ML algorithms and select the suitable one based on the application.<\/li>\n<\/ol>\n<p align=\"justify\">For detailed syllabus of all other subjects of Artificial Intelligence &amp; Data Science, 2021 regulation curriculum do visit <a class=\"rank-math-link\" href=\"..\/category\/ai-ds+4th-sem\">AI&amp;DS 4th Sem subject syllabuses for 2021 regulation<\/a>. <\/p>\n<p align=\"justify\">For all Artificial Intelligence &amp; Data Science results, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-results\/\">Anna University AI&amp;DS all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine Learning Laboratory detailed syllabus for Artificial Intelligence &amp; Data Science (AI&amp;DS) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&amp;DS [&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":[47,144],"tags":[],"class_list":["post-50614","post","type-post","status-publish","format-standard","hentry","category-4th-sem","category-aids"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/50614","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=50614"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/50614\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=50614"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=50614"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=50614"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}