Computer vision and OpenCV[edit | edit source]
Machine learning[edit | edit source]
- https://medium.com/machine-learning-in-practice/over-200-of-the-best-machine-learning-nlp-and-python-tutorials-2018-edition-dd8cf53cb7dc
- http://web.archive.org/web/20201204051345/https://www.kaggle.com/kanncaa1/data-sciencetutorial-for-beginners
- http://web.archive.org/web/20201112012411/https://www.kaggle.com/kanncaa1/machine-learning-tutorial-for-beginners
Classic Texts[edit | edit source]
There are also a number of classical books for both topics:
- Richard Szeliski. Computer Vision: Algorithms and Applications. Springer, 2010.
http://szeliski.org/Book/drafts/SzeliskiBook_20100903_draft.pdf
- Gary Bradski and Adrian Kaehler. Learning OpenCV. O'Reilly, 2008.
https://www.bogotobogo.com/cplusplus/files/OReilly%20Learning%20OpenCV.pdf
- Ian Goodfellow, Yoshua Bengio and Aaron Courville. Deep Learning. MIT Press, 2016.
https://github.com/janishar/mit-deep-learning-book-pdf
- Christopher Bishop. Pattern recognition and machine learning. Springer, 2006.
