Practical Machine Learning With Rust
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Practical Machine Learning With Rust
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Author : Joydeep Bhattacharjee
language : en
Publisher: Apress
Release Date : 2019-12-10
Practical Machine Learning With Rust written by Joydeep Bhattacharjee and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-10 with Mathematics categories.
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.
Machine Learning With Rust
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Author : Keiko Nakamura
language : en
Publisher: GitforGits
Release Date : 2024-01-31
Machine Learning With Rust written by Keiko Nakamura and has been published by GitforGits this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-31 with Computers categories.
In this stimulating journey of Rust, you'll learn how to use the Rust programming language in conjunction with machine learning. It's not a full guide to learning machine learning with Rust. Instead, it's more of a journey that shows you what's possible when you use Rust to solve machine learning problems. Some people like Rust because it is quick and safe. This book shows how those qualities can help machine learning a lot. To begin, we will show you what Rust is and how it works. This is so that everyone, even those who are new to Rust, can follow along. Then, we look at some basic machine learning concepts, such as linear and logistic regression, and show how to use Rust's tools and libraries to make these ideas work. You will learn more complex techniques like decision trees, support vector machines, and how to work with data as we go along. It goes all the way up to neural networks and image recognition, and we show you how to use Rust for these types of tasks step by step. We use real-world examples, such as COVID data and the CIFAR-10 image set, to show how Rust works with issues that come up in the real world. This book is all about discovery and experimentation. To see what you can do with them, we use various Rust tools for machine learning. It's a fun way to see how Rust can be used in machine learning, and it will make you want to try new things and learn more on your own. This is only the beginning; there is so much more to uncover as you continue to explore machine learning with Rust. Key Learnings Exploit Rust's efficiency and safety to construct fast machine learning models. Use Rust's ndarray crate for numerical computations to manipulate complex machine learning data. Find out how Rust's extensible machine learning framework, linfa, works across algorithms. Use Rust's precision and speed to construct linear and logistic regression. See how Rust crates simplify decision trees and random forests for prediction and categorization. Learn to implement and optimize probabilistic classifiers, SVMs and closest neighbor methods in Rust. Use Rust's computing power to study neural networks and CNNs for picture recognition and processing. Apply learnt strategies to COVID and CIFAR-10 datasets to address realistic problems and obtain insights. Table of Content Rust Basics for Machine Learning Data Wrangling with Rust Linear Regression by Example Logistic Regression for Classification Decision Trees in Action Mastering Random Forests Support Vector Machines in Action Simplifying Naive Bayes and k-NN Crafting Neural Networks with Rust
Practical Rust Projects
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Author : Shing Lyu
language : en
Publisher: Apress
Release Date : 2020-02-27
Practical Rust Projects written by Shing Lyu and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-27 with Computers categories.
Go beyond the basics and build complete applications using the Rust programming language. The applications in this book include a high-performance web client, a microcontroller (for a robot, for example), a game, an app that runs on Android, and an application that incorporates AI and machine learning. Each chapter will be organized in the following format: what this kind of application looks like; requirements and user stories of our example program; an introduction to the Rust libraries used; the actual implementation of the example program, including common pitfalls and their solutions; and a brief comparison of libraries for building each application, if there is no clear winner. Practical Rust Projects will open your eyes to the world of practical applications of Rust. After reading the book, you will be able to apply your Rust knowledge to build your own projects. What You Will Learn Write Rust code that runs on microcontrollers Build a 2D game Create Rust-based mobile Android applications Use Rust to build AI and machine learning applications Who This Book Is For Someone with basic Rust knowledge, wishing to learn more about how to apply Rust in a real-world scenario.
Multivariate Statistical Machine Learning Methods For Genomic Prediction
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Author : Osval Antonio Montesinos López
language : en
Publisher: Springer Nature
Release Date : 2022-02-14
Multivariate Statistical Machine Learning Methods For Genomic Prediction written by Osval Antonio Montesinos López and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-14 with Technology & Engineering categories.
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Mastering Machine Learning With Rust
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Author : PHILLIPS. JEREMY
language : en
Publisher: Independently Published
Release Date : 2025-04-24
Mastering Machine Learning With Rust written by PHILLIPS. JEREMY and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Computers categories.
Are you a Rust programmer or an AI developer eager to harness the raw power of Rust for machine learning? This book is your hands-on guide to achieving ML mastery with Rust, taking you from foundational concepts to building and deploying high-performance ML systems. Rust is uniquely positioned to tackle the challenges of modern machine learning. Its unparalleled performance, combined with robust memory safety, makes it ideal for crafting resource-efficient and lightning-quick ML applications. This book will teach you how to leverage these advantages. What's Inside: Inside, you'll discover how to: Master Rust's essential features for efficient data handling and manipulation. Implement core machine learning algorithms from scratch, gaining a deep understanding of their inner workings. Utilize Rust's powerful tools for parallel processing and vectorized computations to maximize performance. Build and train neural networks in Rust, optimizing them for speed and efficiency. Deploy your Rust ML models as standalone executables or scalable web APIs. Explore advanced ML techniques and navigate the Rust ML ecosystem. Who is this book for: This book is for Rust programmers looking to apply their skills to machine learning and AI developers seeking to unlock the potential of Rust for high-performance ML. Whether you're a seasoned Rustacean or new to the language, you'll find clear explanations, practical examples, and actionable guidance. The demand for high-performance ML is exploding, and Rust is emerging as a key technology to meet this need. Don't get left behind. This book provides you with a future-proof skillset. Rust empowers you to build machine learning systems that not only meet today's demands but are also ready for the challenges of tomorrow. More than just a language guide, this book is your practical roadmap to building real-world, high-performance ML applications. You'll gain invaluable expertise. Ready to take your machine learning skills to the next level? Embark on this journey of Mastering Machine Learning with Rust, and become a pioneer in the next generation of AI development
Applications Of Artificial Intelligence And Machine Learning
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Author : Bhuvan Unhelker
language : en
Publisher: Springer Nature
Release Date : 2022-09-13
Applications Of Artificial Intelligence And Machine Learning written by Bhuvan Unhelker and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-13 with Computers categories.
The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning—ICAAAIML 2021. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business, and security. This book contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book is a valuable resource for students, academics, and practitioners in the industry working on AI applications.
Availability Reliability And Security In Information Systems And Hci
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Author : Alfredo Cuzzocrea
language : en
Publisher: Springer
Release Date : 2013-08-19
Availability Reliability And Security In Information Systems And Hci written by Alfredo Cuzzocrea and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-19 with Computers categories.
This book constitutes the refereed proceedings of the IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference on Availability, Reliability and Security, CD-ARES 2013, held in Regensburg, Germany, in September 2013. The 21 revised papers presented were carefully reviewed and selected for inclusion in the volume. The papers concentrate on the many aspects of information systems bridging the gap between research results in computer science and the many application fields. They are organized in the following topical sections: economic, ethical, legal, multilingual, organizational and social aspects; context-oriented information integration; data/information management as a service; context-oriented information integration and location-aware computing; security and privacy; risk management and business continuity; and security and privacy and location based applications. Also included are 15 papers from a special session on Human-Computer Interaction and Knowledge Discovery (HCI-KDD 2013).
Rust Programming For Machine Learning
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Author : Tony Bozeman
language : en
Publisher: Independently Published
Release Date : 2025-06-17
Rust Programming For Machine Learning written by Tony Bozeman and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-17 with Computers categories.
Build blazing-fast, robust AI systems-powered by Rust. Are you a machine learning developer tired of struggling with slow performance, complex dependencies, and unsafe code? Looking to boost your AI workflows with a language designed for both speed and safety? Rust Programming for Machine Learning is your practical, hands-on guide to building high-performance, production-ready AI pipelines using Rust, the modern systems language known for combining efficiency, memory safety, and developer productivity. This comprehensive guide introduces Rust specifically through the lens of machine learning, covering every essential aspect-from foundational Rust concepts to deploying optimized machine learning models at scale. You'll learn to construct safe and fast AI systems without sacrificing readability or maintainability. Inside, you'll discover: Foundations of Rust for Machine Learning: Quickly grasp key concepts like ownership, zero-cost abstractions, traits, and effective use of the Rust ecosystem. Data Ingestion and Preprocessing: Master efficient data handling with powerful Rust libraries like serde and ndarray. Implementing Linear Models and Decision Trees: Build models from scratch, using pure Rust for ordinary least squares, gradient descent, and ensemble methods like Random Forests and Gradient Boosting. Crafting Neural Networks: Learn to define layers, activation functions, backpropagation, and serialization to deploy models effectively. GPU Acceleration and Parallelism: Accelerate your AI workflows using CUDA, OpenCL, Rayon, and Rust's async programming to maximize concurrency and throughput. Embedded and Edge AI: Optimize and deploy resource-constrained models to edge devices, microcontrollers, and Raspberry Pi platforms. Model Explainability: Clearly interpret model predictions with practical implementations of LIME, SHAP, and feature-importance visualizations. Production Deployment and Monitoring: Containerize Rust applications using Docker and Kubernetes, instrument systems with Prometheus, and master structured logging and alerting for robust production environments. Whether you're a seasoned AI practitioner or a developer eager to leverage Rust's powerful capabilities, this book provides the practical guidance, best practices, and real-world examples you need to produce efficient, secure, and high-quality machine learning solutions. Ready to build machine learning systems that perform faster, scale reliably, and ensure safety at every step? Get your copy of Rust Programming for Machine Learning today, and start creating exceptional AI solutions-fast, safe, and confidently.
Advances In Bioinformatics And Computational Biology
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Author : Katia S. Guimarães
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-30
Advances In Bioinformatics And Computational Biology written by Katia S. Guimarães and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-30 with Science categories.
This volume contains the papers selected for presentation at the 4th Brazilian Sym- sium on Bioinformatics, BSB 2009, which was held in Porto Alegre, Brazil, during August 29–31, 2009. The BSB symposium had its origins in the Brazilian Workshop on Bioinformatics (WOB). WOB had three editions, in 2002 (Gramado, RS), in 2003 (Macaé, RJ), and in 2004 (Brasília, DF). The change in the designation from wo- shop to symposium reflects the increase in the quality of the contributions and also in the interest of the scientific community for the meeting. The previous editions of BSB took place in São Leopoldo, RS, in 2005, in Angra dos Reis, RJ, in 2007, and in Santo André, SP, in 2008. As evidence of the internationalization of the event, BSB 2009 had 55 submissions from seven countries. Of the 55 papers submitted, 36 were full papers, with up to 12 pages each, and 19 were extended abstracts, with up to 4 pages each. The articles submitted were carefully reviewed and selected by an international Program Comm- tee, comprising three chairs and 45 members from around the world, with the help of 21 additional reviewers. The Program Committee Chairs are very thankful to the - thors of all submitted papers, and especially to the Program Committee members and the additional reviewers, who helped select the 12 full papers and the six extended abstracts that make up this book.
Practical Rust Projects
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Author : Shing Lyu
language : en
Publisher: Apress
Release Date : 2023-08-06
Practical Rust Projects written by Shing Lyu and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-06 with Computers categories.
Go beyond the basics and build complete applications using the Rust programming language, updated for Rust 2021 edition. The applications you'll build over the course of this book include a high-performance web client, an embedded computer (for a robot, for example), a game, a serverless web app, and an application that incorporates AI and machine learning. Each chapter is organized in the following format: what the kind of should application look like; requirements and user stories of our example program; an introduction to the Rust libraries used; the actual implementation of the example program, including common pitfalls and their solutions; and a brief comparison of libraries for building each application, if there is no clear preference. Practical Rust Projects, Second Edition will open your eyes to how Rust can be put to practical, real-world use. After reading this book, you will be able to use Rust to build a variety of your own projects. What You Will Learn Explore practical Rust programming language-based projects, examples and case studies Create a GUI Build a high performance web Front-end using WebAssembly Develop REST APIs using Rust Go serverless to develop a cloud application using the Amazon AWS Rust SDK Create a game using Rust, along with AI and machine learning apps Who This Book Is For Those with basic Rust knowledge who want to learn more about how to apply Rust in real-world scenarios.