Hands-On AI Science is a series of in-depth guides to the major fields of artificial intelligence. Every book goes deep into the theory, models, and internals, covering the classical foundations and the most recent ideas, then shows you how to build each one in Python with the modern libraries and tools that get the job done. The writing stays plain and light (illustrations, analogies, mental models, worked examples, and a little fun) without trading away rigor or coverage. Each volume is self-contained and complete enough to anchor a full course on its subject.
The Books
- Building Language AI: From Tokens to Agents.
- Building Vision AI: From Pixels to Generative Models.
- Building Temporal AI: From Forecasting to Sequential Decision Making.
- Building Scalable AI: From Big Data Algorithms to Distributed Intelligence.
- Building Embodied AI: From Perception to Autonomous Action.
- Building Agentic AI: From Goals to Autonomous Systems.
- Building Discovery AI: From Vibe Coding to Autonomous Science.
- Building Neuromorphic AI: From Spiking Neurons to Edge Intelligence.
- Building Quantum AI: From Qubits to Quantum Machine Learning.
- Building Sensory AI: Machine Perception of the Physical World. (This book.)
Where Building Sensory AI Fits
Where Building Vision AI covers what a camera sees and Building Temporal AI covers how sequences evolve, this volume covers everything else a machine can measure: inertial motion, vibration, radar and lidar returns, depth, heat, radio channels, touch, and the electrical signals of the human body. It treats sensors as instruments with noise, bias, drift, and failure modes rather than as clean arrays, and follows the full chain from raw sample to deployed, trustworthy decision.