The first book on Rust for machine learning
Covers the basics to full-blown applications
Provides insights into challenges when working with the existing ecosystem
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.
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.
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: Usage in other domains.
Chapter 8: Deploying Machine Learning Application.
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.
You will:
- 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
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.
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 den Autor
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.
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.
Klappentext
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.
The first book on Rust for machine learning
Covers the basics to full-blown applications
Provides insights into challenges when working with the existing ecosystem
