Deep Learning with Rust

Mastering Efficient and Safe Neural Networks in the Rust Ecosystem

Häftad, Engelska, 2026

607 kr

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Beskrivning

What You Will LearnUnderstand deep learning foundations and Rust programming principles.Implement and optimize deep learning models in Rust, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs.Develop practical deep learning applications to solve real-world problems, including natural language processing, computer vision, and speech recognition.Explore Rust’s safety features, including its strict type of system and ownership model, and learn strategies to create reliable and secure AI software.Gain an understanding of the broader ecosystem of tools and libraries available for deep learning in Rust.Who This Book Is forA broad audience with varying levels of experience and knowledge, including advanced programmers with a solid foundation in Rust or other programming languages (Python, C++, and Java) who are interested in learning how Rust can be used for deep learning apps. It may also be suitable for data scientists and AI practitioners who are looking to understand how Rust can enhance the performance and safety of deep learning models, even if they are new to the Rust programming language.

Produktinformation

Utgivningsdatum:2026-02-11
Mått:178 x 254 x 12 mm
Vikt:395 g
Format:Häftad
Språk:Engelska
Antal sidor:182
Förlag:APress
ISBN:9798868822070

Utforska kategorier

Programspråk inom Data och IT
Systemvetenskap och AI inom Data och IT

Mer om författaren

Dr. Mehrdad Maleki holds a Ph.D. in Theoretical Computer Science and a Master’s degree in Mathematics. He is an accomplished AI Scientist and researcher specializing in artificial intelligence, quantum computing, and cybersecurity. His work combines deep mathematical insight with practical engineering to design scalable, high-performance AI and quantum systems.Over the years, Dr. Maleki has led several R&D projects, contributing to more than ten patents in AI and quantum computing. His research and innovations span areas such as deep learning, foundation models, automatic differentiation, and scientific computing. Proficient in Python and Rust, he bridges the gap between theoretical research and real-world applications by transforming complex algorithms into impactful solutions.

Innehållsförteckning

Part I: Foundations of Deep Learning in Rust.- Chapter 1: Introduction.- Chapter 2: Introduction to Deep Learning in Rust.- Chapter 3: Rust Syntax for AI Practitioners (Optional).- Chapter 4: Why Rust for Deep Learning?.- Part II: Advancing with Rust in AI.- Chapter 5: Building Blocks of Neural Networks in Rust .- Chapter 6: Rust Concurrency in AI - Chapter 7: Deep Neural Networks and Advanced Architectures .- Chapter 8: Generative Models and Transformers in Rust.