Machine Learning Revision Book

My Machine Learning Revision Guide which I am creating whilst I learn Machine Learning to showcase my knowledge and also to use as a revision reference for myself and others who which to learn Machine Learning.

Each area of the guide is covered with the theory, written worked example and a coded example of the algorithm or concept being revised.

Content To Cover

Month 1

Week 1 Linear Algebra

https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/

Week 2 Calculus

https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr

Week 3 Probability

https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2

Week 4 Algorithms

https://www.edx.org/course/algorithm-design-analysis-pennx-sd3x

Month 2

Week 1

Learn python for data science

https://www.youtube.com/watch?v=T5pRlIbr6gg&list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU

Math of Intelligence

https://www.youtube.com/watch?v=xRJCOz3AfYY&list=PL2-dafEMk2A7mu0bSksCGMJEmeddU_H4D

Intro to Tensorflow

https://www.youtube.com/watch?v=2FmcHiLCwTU&list=PL2-dafEMk2A7EEME489DsI468AB0wQsMV

Week 2

Intro to ML (Udacity) https://eu.udacity.com/course/intro-to-machine-learning--ud120

Week 3-4

ML Project Ideas https://github.com/NirantK/awesome-project-ideas

Month 3 (Deep Learning)

Week 1

Intro to Deep Learning https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3

Author

🤖 Ryan Maugin

🐦 @techedryan

💌 ryan.maugin@ada.ac.uk