Machine Learning
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Three types of ML: supervised, unsupervised, and reinforcement — and why learning from data beats hand-written rules.
How to study ML and RL efficiently—spaced practice, active recall, and project-based learning.
5 questions after completing the first 7 ML Foundations pages. Check your understanding before continuing.
What to learn before or alongside reinforcement learning—math, programming, and ML basics.
12 questions covering supervised learning, gradient descent, model evaluation, and sklearn. Pass: 9/12.
15 short drill problems covering supervised learning, gradient descent, evaluation, and sklearn.
Supervised learning, regression, classification, gradient descent, and evaluation—before neural networks for RL.