{"id":7527,"date":"2024-04-04T11:01:58","date_gmt":"2024-04-04T11:01:58","guid":{"rendered":"https:\/\/www.inspirenignite.com\/kl\/5307-introduction-to-machine-learning-lab-syllabus-for-robotics-process-automation-5th-sem-2021-revision-sitttr\/"},"modified":"2024-04-04T11:01:58","modified_gmt":"2024-04-04T11:01:58","slug":"5307-introduction-to-machine-learning-lab-syllabus-for-robotics-process-automation-5th-sem-2021-revision-sitttr","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/kl\/5307-introduction-to-machine-learning-lab-syllabus-for-robotics-process-automation-5th-sem-2021-revision-sitttr\/","title":{"rendered":"5307: Introduction To Machine Learning Lab Syllabus for Robotics Process Automation 5th Sem 2021 Revision SITTTR"},"content":{"rendered":"<p align=\"justify\">Introduction To Machine Learning Lab detailed syllabus for Robotics Process Automation (RP) for 2021 revision curriculum has been taken from the <a class=\"rank-math-link\" href=\"http:\/\/www.sitttrkerala.ac.in\/\" style=\"color: inherit\" target=\"_blank\" rel=\"noopener\">SITTTRs<\/a> official website and presented for the Robotics Process Automation 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 Robotics Process Automation 5th Sem scheme and its subjects, do visit <a class=\"rank-math-link\" href=\"..\/sitttr-diploma-robotics-process-automation-rp-syllabus-for-5th-sem-2021-revision\">Robotics Process Automation (RP) 5th Sem 2021 revision scheme<\/a>. The detailed syllabus of introduction to machine learning lab is as follows. <\/p>\n<p><h4>Course Objectives:<\/h4>\n<ul>\n<li>Learn to perform data extraction and preprocessing using python tool kits.<\/li>\n<li>Demonstrate the working of classification and regression algorithms.<\/li>\n<li>Demonstrate the working of clustering algorithms<\/li>\n<li>Understand and analyze the performance of neural networks in classification.<\/li>\n<li>To obtain practical knowledge in real world problems.<\/li>\n<\/ul>\n<p><h4>Course Outcomes:<\/h4>\n<p>On completion of the course student will be able to:<\/p>\n<ol>\n<li>Understand the features of machine learning to apply on real world problems using python programming language.<\/li>\n<li>Understand the different types of Classification and regression algorithms.<\/li>\n<li>Design and evaluate the unsupervised models through python in built functions.<\/li>\n<li>Analyze the concepts of perceptron and SVM and implement using python packages.<\/li>\n<\/ol>\n<p><h4>Module 1:<\/h4>\n<ol>\n<li>Study of Python Basic Libraries such as Statistics, Math, Numpy and Scipy<\/li>\n<li>Study of Python Libraries for ML application such as Pandas and Matplotlib<\/li>\n<\/ol>\n<p><h4>Module 2:<\/h4>\n<ol>\n<li>Preprocess the dataset<\/li>\n<li>Implementation of Bayesian classifier and analyzing the classification performance.<\/li>\n<li>Implementation of simple and linear regression using python built in functions.<\/li>\n<li>Implementation of multiple linear regression using python built in functions.<\/li>\n<\/ol>\n<p><h4>Module 3:<\/h4>\n<ol>\n<li>Implement K-means clustering algorithm to cluster a set of data stored in a csv file<\/li>\n<li>Implement EM clustering algorithm to cluster a set of data stored in a csv file<\/li>\n<\/ol>\n<p><h4>Module 4:<\/h4>\n<ol>\n<li>Implement perceptron classifier using python sklearn<\/li>\n<li>Implement SVM classifier using python sklearn<\/li>\n<li>Performance analysis of classification algorithms on a specific dataset.<\/li>\n<\/ol>\n<p><h4>Micro Project<\/h4>\n<p>Students are expected to do a micro project in machine learning during the course for the purpose of continuous evaluation. This experiment shall be included in the bona-fide record. Example: Develop program such as<\/p>\n<ul>\n<li>Classification of Mushroom dataset (UCI repository)<\/li>\n<li>House price prediction (Regression)<\/li>\n<li>K-Means clustering (Iris dataset)<\/li>\n<\/ul>\n<p><h4>Text Books:<\/h4>\n<ol>\n<li>Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006<\/li>\n<li>Ethem Alpayd\u00c4\u00b1n, Introduction to Machine Learning (Adaptive Computation and Machine Learning), MIT Press, 2004.<\/li>\n<\/ol>\n<p><h4>Online Resources<\/h4>\n<ol>\n<li>https:\/\/www.javatpoint.com\/machine-learning<\/li>\n<li>https:\/\/www.toptal.com\/machine-learning\/machine-learning-theory-an-introductory primer<\/li>\n<li>https:\/\/www.tutorialspoint.com\/machine_learning\/index.htm<\/li>\n<li>https:\/\/ml-course.github.io\/master\/labs\/Lab%201%20-%20Tutorial<\/li>\n<li>https:\/\/www.geeksforgeeks.org\/introduction-machine-learning-using-python\/<\/li>\n<\/ol>\n<p><h4><H4>List of Experiments:<\/H4><\/h4>\n<ol>\n<li>Write a python program to demonstrate the working of Numpy functions.<\/li>\n<li>Write a python program to demonstrate the working of math library functions.<\/li>\n<li>Write a python program to read data from a csv file and convert it to pandas data frame.<\/li>\n<li>Write a python program to plot graphs using Matplotlib library.<\/li>\n<li>Write a python program to preprocess the dataset by substituting mean, mode or median for missing data.<\/li>\n<li>Write a python program to implement a Bayesian classifier and analyze the classification performance.<\/li>\n<li>Write a python program to implement simple linear regression using built in functions.<\/li>\n<li>Write a python program to implement multiple linear regression using built in functions.<\/li>\n<li>Implement K-means clustering algorithm to cluster a set of data stored in a csv file<\/li>\n<li>Implement EM clustering algorithm to cluster a set of data stored in a csv file<\/li>\n<li>Implement perceptron classifier using python sklearn<\/li>\n<li>Implement SVM classifier using python sklearn<\/li>\n<li>Write a python program to do the performance analysis of classification algorithms on a specific dataset.<\/li>\n<\/li>\n<\/ol>\n<p align=\"justify\">For detailed syllabus of all other subjects of Robotics Process Automation (RP), 2021 revision curriculum do visit <a class=\"rank-math-link\" href=\"..\/category\/sitttr\/rp\">Robotics Process Automation 5th Sem subject syllabuses for 2021 revision<\/a>. <\/p>\n<p align=\"justify\">To see the syllabus of all other branches of diploma 2021 revision curriculum do visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/kl\/sitttr-syllabus\/\"> SITTTR diploma all branches syllabus.<\/a>. <\/p>\n<p align=\"justify\">To see the results of Robotics Process Automation (RP) of diploma 2021 revision curriculum do visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/kl\/sitttr-results\/\"> SITTTR diploma Robotics Process Automation (RP) results.<\/a>. <\/p>\n<p align=\"justify\">For all Robotics Process Automation academic calendars, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/kl\/sitttr-academic-calendar\/\"> Robotics Process Automation all semesters academic calendar<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Introduction To Machine Learning Lab detailed syllabus for Robotics Process Automation (RP) for 2021 revision curriculum has been taken from the SITTTRs official website and presented for the Robotics Process [&hellip;]<\/p>\n","protected":false},"author":2462,"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":[36,90],"tags":[],"class_list":["post-7527","post","type-post","status-publish","format-standard","hentry","category-5th-sem","category-rp"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/posts\/7527","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/users\/2462"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/comments?post=7527"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/posts\/7527\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/media?parent=7527"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/categories?post=7527"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/kl\/wp-json\/wp\/v2\/tags?post=7527"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}