AI & Machine Learning

StatQuest with Josh Starmer

Reinforcement Learning with Human Feedback (RLHF) aligns large language models to produce helpful, polite responses by training a reward model on human preference comparisons, solving the overfitting and cost limitations of supervised fine-tuning.

StatQuest with Josh Starmer

This video provides a step-by-step mathematical walkthrough of policy gradient reinforcement learning, demonstrating how to derive gradients via the chain rule and use binary reward signals (+1/-1) to correct update directions when training neural networks without labeled data.

StatQuest with Josh Starmer

This video explains how policy gradients enable neural network training without known target values by guessing actions, observing environmental rewards, and using those rewards to correct the direction of gradient descent updates.