Publisher's Synopsis
Reactive Publishing
Rust for Data Science: A Practical Guide to High-Performance Analytics
Speed. Safety. Scalability.
Welcome to the next evolution of data science.
As datasets grow and performance bottlenecks hit hard, traditional tools can fall short. Enter Rust-a systems programming language built for blazing-fast performance, memory safety, and rock-solid reliability. This book bridges the worlds of data science and systems engineering, giving you the tools to build powerful, efficient analytics pipelines without sacrificing control or speed.
Inside, you'll explore:
Why Rust matters for modern data science and analytics workflows
Building custom data processing pipelines in Rust
How Rust integrates with Python, Polars, Apache Arrow, and more
Real-time, low-latency processing for streaming and big data use cases
Hands-on projects to implement statistical models, transformations, and visualizations
Whether you're a Python veteran ready to level up your backend or a systems developer entering the world of analytics, this guide provides the practical, end-to-end knowledge to bring your data workflows into the Rust ecosystem.
Rust isn't just fast. It's the future of high-performance data science.
Build smarter. Analyze deeper. Execute faster.
