Are you interested in quickly yet comprehensively learn-by-computational-training the math behind neural networks and other machine learning algorithms, and implement ideas from scratch in Python/R so that you can get a great head start for projects and courses such as CS231n, CS230, and CS229?

I was a multiple-teaching-award-winning instructor at Stanford with deep experience in several math-related courses and am currently running machine learning projects in a research & academic setup on survival analysis and gait analysis, to mention a couple. I have successfully helped several full- and part-time students from Stanford and the Bay Area industry to navigate the mathematical maze behind machine learning with ease and enjoy applying machine learning to practical problems. Meeting sessions can be tailored to your specific background and needs.

I'm offering online tutoring service for strengthening math fundamentals (linear algebra, matrix calculus, probability, and statistics) required for CS229, CS224n, CS230, CS231n, and other machine learning-related courses. I can also help with Python and R programming for machine learning-related projects.

I also specialize in teaching the following courses:

• Multivariable Calculus (CME 100, Math 51, Math 52, Math 53)
• ODEs & PDEs (CME 102, CME 104, CME 108, CME 204, CME 206, CME 306)
• Linear Algebra (CME 103, Math 51, Math 104, Math 113, CME 302)
• Optimization (MS&E 111/211)
• Probability (MS&E 121/221, CS 109, Stats 116)
• Analysis (Math 115)

and other programming related (MATLAB, C/C++, Python, Julia) courses.

My rate is $50 per hour, and meetings will be via Google Meet. Please get in touch if interested.

P.S. : the image above shows the weights learned by a linear classifier trained on the fashion-dataset.