Ml lab manual vtu

​ COURSE DESCRIPTION

Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers the theory and practical algorithms for machine learning from a variety of perspectives. We cover topics such as FIND-S , Candidate Elimination Algorithm , Decision tree (ID3 Algorithm) , Backpropagation Algorithm , Naïve Bayesian classifier , Bayesian Network , k-Means Algorithm , k-Nearest Neighbour Algorithm , Locally Weighted Regression Algorithm .

​ COURSE OBJECTIVES

  1. Make use of Data sets in implementing the machine learning algorithms
  2. Implement the machine learning concepts and algorithms in any suitable language of
    choice.

​ COURSE OUTCOMES

  1. Understand the implementation procedures for the machine learning algorithms
  2. Design Java/Python programs for various Learning algorithms.
  3. Apply appropriate data sets to the Machine Learning algorithms
  4. Identify and apply Machine Learning algorithms to solve real world problems
LAB EXPERIMENTS

1. Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file