{"id":22996,"date":"2020-07-16T06:56:50","date_gmt":"2020-07-16T06:56:50","guid":{"rendered":"https:\/\/www.inspirenignite.com\/jntuh\/cs604pc-machine-learning-lab-cse-syllabus-for-btech-3rd-year-2nd-sem-r18-regulation-jntuh\/"},"modified":"2020-07-16T06:56:50","modified_gmt":"2020-07-16T06:56:50","slug":"cs604pc-machine-learning-lab-cse-syllabus-for-btech-3rd-year-2nd-sem-r18-regulation-jntuh","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/jntuh\/cs604pc-machine-learning-lab-cse-syllabus-for-btech-3rd-year-2nd-sem-r18-regulation-jntuh\/","title":{"rendered":"CS604PC: Machine Learning Lab CSE Syllabus for B.Tech 3rd Year 2nd Sem R18 Regulation JNTUH"},"content":{"rendered":"

Machine Learning Lab detailed Syllabus for Computer Science & Engineering (CSE), R18 regulation has been taken from the 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

For all other CSE 3rd Year 2nd Sem Syllabus for B.Tech R18 Regulation JNTUH, do visit CSE 3rd Year 2nd Sem Syllabus for B.Tech R18 Regulation JNTUH <\/a>Subjects. The detailed Syllabus for machine learning lab is as follows. <\/p>\n

Course Objectives:<\/h4>\n

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App<\/a>
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b>
\"Get<\/a>. <\/p>\n

Course Outcomes:<\/h4>\n

\nAfter the completion of the course the student can able to:<\/p>\n

    \n
  1. understand complexity of Machine Learning algorithms and their limitations;<\/li>\n
  2. understand modern notions in data analysis-oriented computing;<\/li>\n
  3. be capable of confidently applying common Machine Learning algorithms in practice and implementing their own;<\/li>\n
  4. Be capable of performing experiments in Machine Learning using real-world data.<\/li>\n<\/ol>\n

    List Of Experiment:<\/h4>\n

    \n

      \n
    1. The probability that it is Friday and that a student is absent is 3 %. Since there are 5 school days in a week, the probability that it is Friday is 20 %. What is theprobability that a student is absent given that today is Friday? Apply Bayes rule in python to get the result. (Ans: 15%)<\/li>\n
    2. Extract the data from database using python<\/li>\n
    3. Implement k-nearest neighbours classification using python<\/li>\n
    4. Given the following data, which specify classifications for nine combinations of VAR1 and VAR2 predict a classification for a case where VAR1=0 . 906 and VAR2=0 . 606, using the result of k-means clustering with 3 means (i.e., 3 centroids)
      \n Var1 Var2 Class<\/strong>
      \n 1 . 713 1 . 586 0
      \n 0 . 180 1 . 786 1
      \n 0 . 353 1 . 240 1
      \n 0 . 940 1 . 566 0
      \n 1 . 486 0 . 759 1
      \n 1 . 266 1 . 106 0
      \n 1 . 540 0 . 419 1
      \n 0 . 459 1 . 799 1
      \n 0 . 773 0 . 186 1<\/li>\n
    5. The following training examples map descriptions of individuals onto high, medium and low credit-worthiness.
      \n medium skiing design single twenties no -> highRisk
      \n high golf trading married forties yes -> lowRisk
      \n low speedway transport married thirties yes -> medRisk
      \n medium football banking single thirties yes -> lowRisk
      \n high flying media married fifties yes -> highRisk
      \n low football security single twenties no -> medRisk
      \n medium golf media single thirties yes -> medRisk
      \n medium golf transport married forties yes -> lowRisk
      \n high skiing banking single thirties yes -> highRisk
      \n low golf unemployed married forties yes -> highRisk
      \n Input attributes are (from left to right) income, recreation, job, status, age-group, home-owner. Find the unconditional probability of ‘golf and the conditional probability of ‘single’ given ‘medRisk’ in the dataset?<\/li>\n
    6. Implement linear regression using python.<\/li>\n
    7. Implement Naive Bayes theorem to classify the English text<\/li>\n
    8. Implement an algorithm to demonstrate the significance of genetic algorithm<\/li>\n
    9. Implement the finite words classification system using Back-propagation algorithm<\/li>\n<\/ol>\n

      For detail Syllabus of all other subjects of B.Tech 3rd Year Computer Science & Engineering, visit CSE 3rd Year Syllabus<\/a> Subjects.<\/p>\n

      For all B.Tech results, visit JNTUH B.Tech all years, and semester results <\/a>from direct links.<\/p>\n","protected":false},"excerpt":{"rendered":"

      Machine Learning Lab detailed Syllabus for Computer Science & Engineering (CSE), R18 regulation has been taken from the JNTUH official website and presented for the students affiliated to JNTUH course […]<\/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":[122,2],"tags":[],"class_list":["post-22996","post","type-post","status-publish","format-standard","hentry","category-3rd-year","category-cse"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts\/22996","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\/2344"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/comments?post=22996"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts\/22996\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/media?parent=22996"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/categories?post=22996"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/tags?post=22996"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}