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How to get from high school math to cutting-edge ML/AI
1) Foundational math. 2) Classical machine learning. 3) Deep learning. 4) Cutting-edge machine learning.
First, students implemented basic ML algorithms from scratch, coding up streamlined versions of polynomial and logistic regression, k-nearest neighbors, k-means clustering, and parameter fitting via gradient descent. Then, they implemented more advanced ML algorithms such as decision trees and neural networks (still streamlined versions), and they reproduced academic research papers in artificial intelligence leading up to Blondie24, an AI computer program that taught itself to play checkers. Yeah, I completely agree that the sheer mountain of work ahead of you can be discouraging, so it is definitely worth doing things to keep your interest alive: reading some articles about the cutting edge, toying around with new machine learning models/libraries, etc.
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