• Instructor: Parimala Kancharla: (office: A17.03.06, email: parimala@iitmandi.ac.in)
  • Office Hours: (or by appointment)
  • Discussion Forum: Piazza code-ds413 ,To Join
  • Class Venue: A18-1
  • Class Timings: A-slot
  • Syllabus
  • TAs
    1. Pallav Dwivedi (s23104@students.iitmandi.ac.in)
    2. Siddharath Shakya (s23048@students.iitmandi.ac.in)
    3. Shilpa Chandra (S22004@students.iitmandi.ac.in)
    4. Soujatya Sarkar (s23106@students.iitmandi.ac.in)
    5. Kriti Khare (s23069@students.iitmandi.ac.in)

    Evaluation

  • Assignments - 25%
  • Tutorials/Quizzes - 15%
  • Take home questions (Open book)- 5%
  • Midsem - 25%
  • Endsem - 30%

    • Resources

    S.N Topic Slides Notes External References
    1. Introduction Slides ..
    1. ML Vs LLMs
    2. Traditional AI Vs Deep Learning
    2. Basic Math Review Slides Notes
    1. Is Relu Differentiable?
    2. RELU is not differentiable,why?
    3. Numerical Computation
    3. Basic Math Continuation Slides Notes ..
    4. Basics of Probability Slides ..
    1. Basics of Probability
    2. Probablity chapter from Deep learning by Ian Goodfellow
    5. Linear Regression Slides
    1. Notes
    2. Class Notes
    1. Textbook-The Elements of Statistical Learning-Chapter-3
    2. PRML-Textbook- Bishop-Chapter-3
    6. Polynomial Regression Slides
    1. Notes
    2. Class Notes
    1. PRML-Textbook- Bishop-Chapter-1
    7. Ridge and Lasso Regression Slides
    1. Notes
    2. Class Notes
    1. Textbook-The Elements of Statistical Learning-Chapter-3
    2. Why L1-regularization gives us sparse models
    8. Q.N on Lasso and Ridge Regression .. Notes Visualization of regularization
    9. Least squares solution for classification Slides Notes
    1. External References-I
    2. External References-II
    3. Bishop Texbook - Chapter 4.1.2
    10. Bias Variance Tradeoff Slides Notes
    1. External References-I
    2. External References-II, Chapter-3 (Page number 147)

    Assignments

    S.N Assignmnet Release Date Submission Date
    1. Assignment-1 17/08/2024 31/08/2024

    Text books

    1. Pattern Recognition and Machine Learning Book by Christopher Bishop Link
    2. Introduction to Machine Learning by Ethem Alpaydin Link
    3. The Elements of Statistical Learning by Trevor Hastie Robert Tibshirani Jerome Friedman Link

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