Are you interested in:

• quickly yet comprehensively learn-by-computational-training the math (linear algebra, probability, and statistics) behind deep and reinforcement learning models?

• effective learning to code using state-of-the-art tools (Tensorflow Functional & Sequential Models, RLlib Reinforcement Learning Library, R tools such as MICE, GLMNET) applied to real-life data?

• physics-informed machine learning?

I was a multiple-teaching-award-winning instructor at Stanford and currently a faculty of applied statistics working on several projects involving deep learning applications in industrial anomaly detection, computer vision, and sports analysis. I have helped several full- and part-time students from Stanford and the Bay Area industry to ace courses & projects at Stanford and smoothly navigate the mathematical maze behind probability, statistics, optimization, linear algebra, and machine learning. Meeting sessions can be tailored to your specific background and needs.

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