WRWei Ruiinintuitiveml.hashnode.dev·Sep 24 · 12 min readA Software Engineer's Intuition for Gradient Descent, Part 2: The Step SizeIn Part 1 we built gradient descent around one update rule: $$\theta := \theta - \alpha \nabla f(\theta)$$ Almost all of that article was about the gradient ∇f(θ), the part that tells us which way is 00
WRWei Ruiinintuitiveml.hashnode.dev·Sep 24 · 9 min readA Software Engineer's Intuition for Gradient DescentFor those of us who have spent years building deterministic software systems, the machine learning realm can feel like a parallel universe. In traditional software engineering, we write the exact rule00
WRWei Ruiinintuitiveml.hashnode.dev·Jun 11 · 14 min readTigers, Ghosting, and Bayes' TheoremTigers, Ghosting, and Bayes' Theorem Prior, likelihood, posterior — and the tug-of-war between them, built from scratch You jolt awake in the dark and hear a tiger roar. For about half a second, what 00
WRWei Ruiinintuitiveml.hashnode.dev·May 25 · 11 min readLogistic Regression is Just Linear Regression with a Midlife CrisisLogistic Regression is Just Linear Regression with a Midlife Crisis The intuition behind logistic regression, built from scratch If you've been learning machine learning, you've probably experienced t00
