Logo
  • Faculty & Staff
  • Training & Placement
  • Student Activities
  • Alumni
  1. ENEnglishहिंहिंदी
  2. Quick Search...Ctrl K
  3. Login
    • Faculty & Staff
    • Training & Placement
    • Student Activities
    • Alumni
    institute

    Institute→

    • Administration

      Meet the leadership team guiding our institution.

    • Sections

      Explore the various sections that support campus life and academics.

    • Campus Infrastructure

      Discover the state-of-the-art facilities and infrastructure on campus.

    • Hostels

      Information about on-campus accommodation and hostel facilities.

    • IKS Cell

      Explore the minds that work hard to maintain our institute’s high reputation and proper functioning!

    • IIC Cell

      Explore the minds that work hard to maintain our institute’s high reputation and proper functioning!

    • IPR Cell

      The Intellectual Property Rights Cell promotes awareness and assists in protecting innovations, ideas, and creative works.

    academics

    Academics→

    • Departments

      Explore the diverse academic departments and their offerings.

    • Programmes

      Discover our range of undergraduate and postgraduate programmes.

    • Courses & Curricula

      Browse through the detailed list of courses available.

    • Convocation

      Get information on upcoming convocation ceremonies.

    • Awards

      Recognizing excellence in academics, research, and beyond.

    • Scholarship

      Learn about scholarships, eligibility, and application details.

    • Academic Notifications

      Stay updated with the latest academic announcements and deadlines.

    research

    Research→

    • Sponsored Projects

      Externally funded sponsored research projects addressing real-world challenges and advancing knowledge.

    • Research and Consultancy

      Research and development across diverse fields, from advanced technologies to social sciences, driving innovation and societal impact.

    • Memorandum of Understanding

      Collaborations and partnerships through signed MoUs with leading institutions, industries, and organizations worldwide.

    • Patents & Technologies

      Patents and developed technologies that showcase the institute's innovation and contribution to industry and academia.

    • Copyrights & Designs

      Registered copyrights and industrial designs reflecting creative and original contributions across various domains.

    • Important Resources

      Key resources, guidelines, and documents supporting research, consultancy, and intellectual property activities.

    Login
Logo
National Institute of Technology, Kurukshetra
Thanesar, Haryana, India 136119
Artwork
Quick Access
  • Campus Infrastructure
  • Hostels
  • Administration
  • Estate Section
  • Accounts Section
  • Library Resources
  • Medical Facilities
Academic Resources
  • Academic Notifications
  • Scholarships
  • Awards
  • Curricula
  • Department Achievements
  • Laboratory Facilities
  • Research Publications
Important Links
  • Faculty & Staff
  • Training & Placement
  • Student Activities
  • Library Committee
  • Membership Privileges
  • Research Scholars
  1. © 2025 National Institute of Technology Kurukshetra. All Rights Reserved.

    CSOE303 Machine Learning

    Prerequisites:

    No prerequisites for this course

    Course Nature: OE
    Objectives:
  1. Be able to understand and apply supervised and unsupervised learning algorithms.
  2. Understand the fundamental concepts in machine learning and popular machine learning algorithms.
  3. Interpretation of data and results using statistics and analysis
  4. Be able to 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

    ChariotHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorseHorse

    Outcomes

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

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

    5. Introduction to Machine Learning Edition 2, by Ethem Alpaydin.