17 technical books on transformers, deep learning, probability and the systems they run on. Every idea arrives three ways at once: the equation, the code, and a diagram you can touch.
That headline was written one word at a time, each picked from a probability distribution. Behind it is a loss surface: click anywhere to drop a ball and watch gradient descent find a valley.
17 volumes. Pull one off the shelf.
355 chapters and 1834 lessons, from the maths underneath to training models at scale.
Data Structures & Algorithms
Master data structures and algorithms from fundamentals to advanced topics. Interactive visualizations, multi-language implementations (C, Python, C++, TypeScript), and real-world applications with interview preparation.
8 chapters · 41 lessons
Look inside a real transformer.
This is the model the books build with you: a small GPT with every matrix and every neuron on screen. Step through the forward pass, switch to the neuron view, change the sentence. Nothing here is a video.
Open the lesson it comes fromOne idea, three ways at once.
This is how every lesson is built. Pick a piece of the attention formula and watch the same piece light up in the code and in the picture.
The equation
The code
# one attention headscores = Q @ K.Tscores = scores / math.sqrt(d_k)weights = softmax(scores, dim=-1)out = weights @ V
The picture
Every query is compared with every key: one score per pair of tokens.
Start with one chapter tonight.
Open the free sample chapter. No card needed.