REFERENCES

[SH] Chirag Shah A Hands-on Introduction to Machine Learning

[ST] Gilbert Strang - Introduction to Linear Algebra sixth Edition-WELLESLEY -CAMBRIDGE PRESS (2023) Note there are significant changes compared to 5. edition.

[PM] Paulsen & Moslund: Introduction to Medical Image Analysis. (https://www.saxo.com/dk/introduction-to-medical-image-analysis_paperback_9783030393632) - (See Matrials)

[DW] Lecture Notes for Introduction to Machine Learning. Dan Witzner Hansen, 2024 (Available from Materials in LearnIT)

[HE] Introduction to Machine Learning and Data Mining Tue Herlau, Mikkel N. Schmidt and Morten Mørup https://gitlab.compute.dtu.dk/tuhe/books/-/raw/main/02450_Book.pdf

[PR] Understanding Deep Learning https://github.com/udlbook/udlbook/releases/download/v4.0.4/Understanding_Deep_Learning.pdf

[STV] Gilbert Stangs Video Lectures on Linear Algebra https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010/video_galleries/video-lectures/

[SO] Programming Computer Vision with Python. Jan Erik Solem.

[DI] https://mml-book.github.io/book/mml-book.pdf

[MU] Probabilistic Machine Learning: An IntroductionKevin Patrick Murphy. MIT Press, March 2022.

[BI] Bishop - Pattern Recognition And Machine Learning - Springer 2006.

[BK] http://www.databookuw.com/

Python links

API docs: https://docs.python.org/3.10

Style guide (for better looking Python code): https://www.python.org/dev/peps/pep-0008/

Numpy user guide https://numpy.org/doc/stable/user/index.html

Matplotlib user guide https://matplotlib.org/users/index.html

scikit-learn https://scikit-learn.org/stable/