Stanford University
Instructor: Andrew Ng
I'm self-learning this class through YouTube to
- Take a step further and explore more about machine learning.
- Get a head start on concepts to my ML classes next quarter, so I will be more prepared.
I'll gain a more thorough understanding by learning from supplementary materials from CS 189 (Introduction to Machine Learning) at UC Berkeley, 10-601 at CMU (Introduction to Machine Learning), and EECS 127 at UC Berkeley (Optimization Models in Engineering).
To get a solid understanding of course material, I am also doing the following activities during the winter break:
- Review Linear Algebra concepts through MIT's 18.06, taught by Prof. Gilbert Strang.
- Review Multivariable Calculus concepts through Stanford Math 51 Notes.
- Review Probability concepts through the textbook A First Course in Probability.