Practical Machine Learning with Rust

Creating Intelligent Applications in Rust
1. Auflage 2019
ISBN: 978-1-4842-5120-1
Verlag: Apress

Buch, Englisch, 354 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 563 g

Explore machine learning in Rust and learn about the intricacies of creating machine learning applications. This book begins by covering the important concepts of machine learning such as supervised, unsupervised, and reinforcement learning, and the basics of Rust. Further, you’ll dive into the more specific fields of machine learning, such as computer vision and natural language processing, and look at the Rust libraries that help create applications for those domains. We will also look at how to deploy these applications either on site or over the cloud.

After reading Practical Machine Learning with Rust, you will have a solid understanding of creating high computation libraries using Rust. Armed with the knowledge of this amazing language, you will be able to create applications that are more performant, memory safe, and less resource heavy.

What You Will Learn

• Write machine learning algorithms in Rust
• Use Rust libraries for different tasks in machine learning
• Create concise Rust packages for your machine learning applications
• Implement NLP and computer vision in Rust
• Deploy your code in the cloud and on bare metal servers

Who This Book Is For 

Machine learning engineers and software engineers interested in building machine learning applications in Rust.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Bhattacharjee, Joydeep

Fachgebiete

• Mathematik | Informatik EDV | Informatik Betriebssysteme Linux Betriebssysteme, Open Source Betriebssysteme
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Chapter 1: Basics of Rust.- Chapter 2: Supervised learning.- Chapter 3: Unsupervised learning and Reinforcement learning.- Chapter 4: Data Processing.- Chapter 5: Natural Language Processing in Rust.- Chapter 6: Computer Vision in Rust.- Chapter 7: Deploying Machine Learning Applications.

Über Autor(innen)

Joydeep Bhattacharjee is a machine learning engineer. He likes creating software tools and processes with a focus on clean code. He is a huge believer in tech and the ability of tech to move the world forward. His expertise includes data exploration, statistical modeling, machine learning algorithms, and data visualization. His is currently working at Nineleaps as a principal engineer.