This chapter outlines why Rust is a compelling choice for deep learning. We focus on Rust’s core strengths—performance, memory safety, and concurrency—and how they address key limitations in Python-based workflows. By emphasizing low-level control, zero-cost abstractions, and data-race-free parallelism, Rust enables faster and safer execution for compute-heavy tasks common in machine learning.