Introduction to Computing

This chapter introduces the computational foundations that underlie machine learning, from the theory of computation to the hardware that executes it.

• Computing Machinery and Intelligence -- Turing machines, computability, complexity, and universal function approximation
• Numerical Computing Hardware -- CPU/GPU architecture, floating point representation, and numerical stability
• From Silicon to PyTorch -- The abstraction stack from hardware to tensor operations, BLAS, and operator fusion
• Parallel and Distributed Computing -- Parallel computing models, Amdahl's law, distributed linear algebra, and communication primitives