From Zero to Agents: A Foundational AI/ML Course, Built From First Principles

By: Junaid Hassan

Most machine learning books ask you to trust the black box. This one doesn't.

From Zero to Agents rebuilds artificial intelligence from first principles - starting at the question of what a word even is to a computer, and ending with a working, tool-using AI agent you build yourself. Every concept is explained three ways: theoretically, mathematically, and in code - first written from scratch in raw Python, then reimplemented in PyTorch, so you always know exactly what the library is doing for you.

This is not a tutorial that skips the hard parts. Every equation is derived. Every result is verified by running the code - including the places where the first attempt didn't work, and the book says so.

Inside, you'll build: Tokenization and embeddings, from raw text to trainable vectorsThe mathematical toolkit - vectors, matrices, gradients, probability - explained through working code, not abstract proofsA complete neural network, with backpropagation derived and verified by handRecurrent networks, LSTMs, and a full transformer with real multi-head attention, trained from scratchLoRA fine-tuning, derived and measured, not just describedA working AI agent - tool use, memory, multi-agent coordination - arriving at the book's own titleWritten for practitioners who want to open a real AI/ML research paper and read the mathematics fluently, on sight - not skim past it to the prose.

• Format: Paperback
• Language: English
• ISBN: B0HHSHT97F
• ISBN13: 9798171126919
• Release Date: September 2026
• Publisher: Independently published
• Length: 334 Pages
• Weight: 0.99 lbs.
• Dimensions: 9.0" x 0.8" x 6.0"