Syllabus
- The lecture notes.
- 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).
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Chapter 3-4 (except 3.6 and 4.4.2)
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Chapter 5 (except 5.2.6, 5.4, 5.5.7)
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Chapter 10 (except 10.4, 10.5, 10.6)
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Chapter 12 (except 12.3.4 and 12.4)
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- 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.no) BUT only for TWO concurrent users
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Chapter 1
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Chapter 2, From beginning up to formula (2.2) p. 23 and section 2.5 (except the formulas)
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Chapter 3 (except the proof of The Perceptron Convergence Theorem in sec. 3.4.1)
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Chapter 4 (except 4.2.6 and the technical details of 4.6)
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Chapter 6, section 6.2 (except 6.2.2)
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Chapter 7, section 7.2 (except subsections 7.2.1-7.2.2)
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Chapter 9, sections 9.1, 9.4-9.6 (except 9.1.1)?
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Chapter 11
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Chapter 13, sections Introduction, 13.2, and 13.3
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Chapter 14, sections 14.1
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- 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)
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Jurafsky and Martin, Speech and language processing, 3rd ed. draft, 30 Dec. 2020
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Chapter 4, sections 4.7- 4.8
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Chapter 5 (except 5.6.2 and the last paragraph of 5.5)
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- Wikipedia
- Artificial Intelligence, sections Introduction, 1, 3, 4, 7.1
- Philosophy of Artificial Intelligence, section 1
- AI effect
Obligatory Mid-Term Exercises (each exercise is PASS/FAIL):
- Passing three programming exercises (in Python) is required to take the exam.
- Students registered for IN4050 will be given additional exercises within area of the course.