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Thanesar, Haryana, India 136119
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  1. © 2025 National Institute of Technology Kurukshetra. All Rights Reserved.

    CSIC301 Machine Learning

    Prerequisites:

    No prerequisites for this course

    Course Nature:
    Objectives:
  1. Understand and apply supervised and unsupervised learning algorithms.
  2. Understand fundamental concepts in machine learning and popular machine learning algorithms.
  3. Interpret data and results using statistics and analysis.
  4. Solve real-life problems using machine learning algorithms with programming in Python.
    5. Similar Courses:

    Course Coordinator

    Dr. Sushil Kumar Madan
    Dr. Sushil Kumar Madan

    Professor

    skmadan@nitkkr.ac.in

    9416292144

    Content

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    Outcomes

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    1. Compare and differentiate among different machine learning techniques.
    2. Implement and analyze regression and classification techniques.
    3. Apply suitable supervised and unsupervised techniques and models for real-life problems and predict outcomes.
    4. Explain the applicability of advanced concepts for recommender systems.
    5. Hands-on problem-solving with programming in Python.
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    Reference Books

    1. M. Pradhan, U. Dinesh Kumar: Machine Learning Using Python, Wiley India, Latest Edition.

    2. J. Han, M. Kamber, J. Pei: Data Mining Concepts and Techniques, Latest Edition.

    3. Christopher Bishop: Pattern Recognition and Machine Learning, 2e.

    4. Tom Mitchell: Machine Learning, First Edition, McGraw-Hill, 1997.

    5. Ethem Alpaydin: Introduction to Machine Learning, 2nd Edition.