JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

MACHINE LEARNING LAB

MCA II Year I Semester (R22)

Course Objective:

  • The objective of this lab is to get an overview of the various machine learning
  • Techniques and can demonstrate them using python.

Course Outcomes:

  • Understand modern notions in predictive data analysis
  • Select data, model selection, model complexity and identify the trends
  • Understand a range of machine learning algorithms along with their strengths and weaknesses
  • Build predictive models from data and analyze their performance

List of Experiments

  • 1. Write a python program to compute Central Tendency Measures: Mean, Median, Mode Measure of Dispersion: Variance, Standard Deviation
  • 2. Study of Python Basic Libraries such as Statistics, Math, Numpy and Scipy
  • 3. Study of Python Libraries for ML application such as Pandas and Matplotlib
  • 4. Write a Python program to implement Simple Linear Regression
  • 5. Implementation of Multiple Linear Regression for House Price Prediction using sklearn
  • 6. Implementation of Decision tree using sklearn and its parameter tuning
  • 7. Implementation of KNN using sklearn
  • 8. Implementation of Logistic Regression using sklearn
  • 9. Implementation of K-Means Clustering
  • 10. Performance analysis of Classification Algorithms on a specific dataset (Mini Project)

TEXT BOOK:

  • 1. Machine Learning – Tom M. Mitchell, - MGH

REFERENCE:

  • 1. Machine Learning: An Algorithmic Perspective, Stephen Marshland, Taylor & Francis

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