Syllabus/achievement requirements

Syllabus

  1. The lecture notes.
  2. A.E. Eiben and J.E. Smith: Introduction to Evolutionary Computing, Second Edition (ISBN 978-3-662-44873-1, available online here when on the UiO network). 
    • Chapter 3-4 (except 3.6 and 4.4.2)

    • Chapter 5 (except 5.2.6, 5.4, 5.5.7)

    • Chapter 10 (except 10.4, 10.5, 10.6)

    • Chapter 12 (except 12.3.4 and 12.4)

  3.  S. Marsland: Machine learning: An Algorithmic Perspective. SECOND EDITION (2015), ISBN: 978-1-4665-8328-3, available online here when on the UiO network (ethernet machine or by logging in through https://vpn.uio.noBUT only for TWO concurrent users
    • Chapter 1

    • Chapter 2, From beginning up to formula (2.2) p. 23 and section 2.5 (except the formulas)

    • Chapter 3 (except the proof of The Perceptron Convergence Theorem in sec. 3.4.1)

    • Chapter 4 (except 4.2.6 and the technical details of 4.6)

    • Chapter 6, section 6.2 (except 6.2.2)

    • Chapter 7, section 7.2 (except subsections 7.2.1-7.2.2)

    • Chapter 9, sections 9.1, 9.4-9.6 (except 9.1.1)?

    • Chapter 11

    • Chapter 13, sections Introduction, 13.2, and 13.3

    • Chapter 14, sections 14.1

  4. Hal Daumé III, A course in Machine Learning
    • Chapter 1, sections 1.0-1.3 (except the pseudo code)
    • Chapter 2, sections 2.2-2.7
    • Chapter 3, sections 3.0-3.3
    • Chapter 5, sections 5.0-5.6 (except precision-recall curves, ROC curves and AUC curves)
  5. Jurafsky and Martin, Speech and language processing, 3rd ed. draft, 30 Dec. 2020

    • Chapter 4, sections 4.7- 4.8

    • Chapter 5 (except 5.6.2 and the last paragraph of 5.5)

  6. Wikipedia

Obligatory Mid-Term Exercises (each exercise is PASS/FAIL):

  1. Passing three programming exercises (in Python) is required to take the exam.
  2. Students registered for IN4050 will be given additional exercises within area of the course.
Published Dec. 28, 2020 4:42 PM - Last modified May 16, 2021 10:59 AM