Fast-reference study notes for Machine Learning, Deep Learning, Reinforcement Learning, and the mathematics behind them — written by hand by a PhD who has taught thousands.
Every page is written by Dr. Milan Joshi — PhD in Mathematics, senior faculty at Great Learning, 20+ years of teaching. No ghostwriters, no AI slop.
You see why a concept matters before you see the equation. Derivations are shown step by step — not collapsed into black boxes.
Dense enough to replace a chapter. Visual enough to scan in minutes. The format you wish your own notes looked like.
The field moves; so do the notes. Every purchase includes every future revision of that set, at no extra cost.
Not walls of prose. Not bullet-point slides. Real handwritten pages where every equation has a box, every derivation flows step by step, and every concept is introduced before it's used.
Ten handwritten pages on gradient descent — from the definition of a derivative to the update rule. No credit card, no fluff.
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The logistic regression note clicked for me in twenty minutes what three months of YouTube videos couldn't. The derivations are the whole thing.
I bought the All-Access bundle before my Google interview loop. Passed. The quick-reference format is exactly what you want the night before.
As a teacher myself, I recommend these to every student. The handwritten format makes hard math approachable without dumbing it down.
