Academic Press 第2页

Hamiltonian Monte Carlo Methods in Machine Learning
by Tshilidzi Marwala(Author), Rendani Mbuvha(Author), Wilson Tsakane Mongwe(Author)
Publisher Finelybook 出版社: Academic Press; (March 2, 2023)
Language 语言: English
pages 页数: 220 pages
ISBN-10 书号: 0443190356
ISBN-13 书号: 9780443190353

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Book Description
Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical issues of variance reduction for parameter estimates of numerous HMC based samplers. The book offers a comprehensive introduction to Hamiltonian Monte Carlo methods and provides a cutting-edge exposition of the current pathologies of HMC-based methods in both tuning, scaling and sampling complex real-world posteriors. These are mainly in the scaling of inference (e.g., Deep Neural Networks), tuning of performance-sensitive sampling parameters and high sample autocorrelation.
Other sections provide numerous solutions to potential pitfalls, presenting advanced HMC methods with applications in renewable energy, finance and image classification for biomedical applications. Readers will get acquainted with both HMC sampling theory and algorithm implementation.

Fullstack Rust: The Complete Guide to Building Apps with the Rust Programming Language and Friends Kindle Edition
by Andrew Weiss(Author), Nate Murray (Editor)
ASIN: B086G767TP
Publication Date 出版日期: March 25, 2020
Language 语言: English
File size: 777 KB
pages 页数: 338 pages

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Book Description
Fullstack Rust: The Complete Guide to Building Apps with the Rust Programming Language and Friends
Learn to build performance-critical Rust apps
The Rust language is a way to write incredibly fast - and safe - code. It's being used to build tools at google, Facebook, Amazon, and many other companies where performance is critical.
While there are some good resources on how to learn the Rust programming language by itself, what these other books don't teach is how to build applications with Rust.
Fullstack Rust solves that. In this book we show you how to use Rust to build incredibly fast web-servers, build command-line tools, and compile apps to run in the browser with Web Assembly (WASM).
Meet the Author: Andy Weiss, Software Engineer at google
I started my career as a Data Scientist and Software Engineer at Facebook before becoming the first engineer at Flexport.
I began working with Rust as a hobby before putting it into production while at Rollbar. I'm now working on Fuchsia at google. In my work, I try to mix the academic rigor from a PhD at Princeton with pragmatism learned from shipping products at companies big and small.
In Fullstack Rust I've put together a book that will show you how to use the Rust ecosystem to build fast, secure, apps and tools.
Learn the techniques and tools to build realistic Rust applications
Rust has features that make it a fantastic tool for a number of tasks. Some highlights include:
Performance
Strong, static, expressive type system
Fearless concurrency
Great error messages
Modern generics
Memory safety
Cross-platform
C interoperability
Compiles to WASM (WebAssembly)
Rust has a great set of documentation around the standard library. However, this book has a different focus - instead of trying to teach you just the Rust language, our goal is to build realistic applications and explore some of the techniques and tools available in Rust for accomplishing those tasks.
In the process of working through some common scenarios, you will also be able to learn Rust.

Research Practitioner's Handbook on Big Data Analytics 1st Edition
by S. Sasikala(Author), D. Renuka Devi(Author), Raghvendra Kumar (Editor)
Publisher Finelybook 出版社: Apple Academic Press; 1st edition (May 4, 2023)
Language 语言: English
pages 页数: 292 pages
ISBN-10 书号: 1774910527
ISBN-13 书号: 9781774910528

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Book Description
This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches.
The book’s authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents a selection of illustrative case studies that show examples of the use of data analytics in industries such as health care, business, education, and social media.

Data Science, Analytics and Machine Learning with R
by Luiz Favero(Author), Patrícia Belfiore(Author), Rafael de Freitas Souza(Author)
Publisher Finelybook 出版社: Academic Press; (February 8, 2023)
Language 语言: English
pages 页数: 660 pages
ISBN-10 书号: 012824271X
ISBN-13 书号: 9780128242711

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Book Description
Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning.
In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear.

Comprehensive Metaheuristics: Algorithms and Applications
by S Ali Mirjalili (Editor), Amir Hossein Gandomi (Editor)
Publisher Finelybook 出版社: Academic Press; (February 16, 2023)
Language 语言: English
pages 页数: 466 pages
ISBN-10 书号: 032391781X
ISBN-13 书号: 9780323917810

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Book Description
Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical prerequisites, and conceptual approaches to provide readers with a solid foundation. After presenting multi-objective optimization, constrained optimization, and problem formation for metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains.
The book takes a much-needed holistic approach, putting the most widely used metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using metaheuristics. New case studies and research problem statements are also discussed, which will help researchers in their application of the concepts.

AIoT Technologies and Applications for Smart Environments (Computing and Networks)
by Mamoun Alazab (Editor), Meenu Gupta (Editor), Shakeel Ahmed (Editor)
Publisher Finelybook 出版社: The Institution of Engineering and Technology (April 12, 2023)
Language 语言: English
pages 页数: 333 pages
ISBN-10 书号: 1839536330
ISBN-13 书号: 9781839536335

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Book Description
Although some IoT systems are built for simple event control where a sensor signal triggers a corresponding reaction, many events are far more complex, requiring applications to interpret the event using analytical techniques to initiate proper actions. Artificial intelligence of things (AIoT) applies intelligence to the edge and gives devices the ability to understand the data, observe the environment around them, and decide what to do best with minimum human intervention. With the power of AI, AIoT devices are not just messengers feeding information to control centers. They have evolved into intelligent machines capable of performing self-driven analytics and acting independently. A smart environment uses technologies such as wearable devices, IoT, and mobile internet to dynamically access information, connect people, materials and institutions, and then actively manages and responds to the ecosystem's needs in an intelligent manner.
In this edited book, the contributors present challenges, technologies, applications and future trends of AIoT in realizing smart and intelligent environments, including frameworks and methodologies for applying AIoT in monitoring devices and environments, tools and practices most applicable to product or service development to solve innovation problems, advanced and innovative techniques, and practical implementations to enhance future smart environment systems. Chapters cover a broad range of applications including smart cities, smart transportation and smart agriculture.
This book is a valuable resource for industry and academic researchers, scientists, engineers and advanced students in the fields of ICTs and networking, IoT, AI and machine and deep learning, data science, sensing, robotics, automation and smart technologies and smart environments.

Principles of Big Graph: In-depth Insight (Volume 128) (Advances in Computers, Volume 128)
by Ripon Patgiri (Editor), Ganesh Chandra Deka (Editor), Anupam Biswas (Editor)
Publisher Finelybook 出版社: Academic Press; (February 9, 2023)
Language 语言: English
pages 页数: 458 pages
ISBN-10 书号: 0323898106
ISBN-13 书号: 9780323898102

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Book Description
Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review.
Fast exact triangle counting in large graphs using SIMD acceleration, A comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data, Big graph based online learning through social networks, Community detection in large-scale real-world networks, Power rank: An interactive web page ranking algorithm, GA based energy efficient modelling of a wireless sensor network, The major challenges of big graph and their solutions: A review, and An investigation on socio-cyber crime graph.

Deep Learning Research Applications for Natural Language Processing
by L. Ashok Kumar (Editor), Dhanaraj Karthika Renuka (Editor), S. Geetha (Editor)
Publisher Finelybook 出版社: Engineering Science Reference (November 10, 2022)
Language 语言: English
pages 页数: 290 pages
ISBN-10 书号: 1668460025
ISBN-13 书号: 9781668460023

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Book Description
Humans have the most advanced method of communication, which is known as natural language. While humans can use computers to send voice and text messages to each other, computers do not innately know how to process natural language. In recent years, deep learning has primarily transformed the perspectives of a variety of fields in artificial intelligence (AI), including speech, vision, and natural language processing (NLP). The extensive success of deep learning in a wide variety of applications has served as a benchmark for the many downstream tasks in AI. The field of computer vision has taken great leaps in recent years and surpassed humans in tasks related to detecting and labeling objects thanks to advances in deep learning and neural networks. Deep Learning Research Applications for Natural Language Processing explains the concepts and state-of-the-art research in the fields of NLP, speech, and computer vision. It provides insights into using the tools and libraries in Python for real-world applications. Covering topics such as deep learning algorithms, neural networks, and advanced prediction, this premier reference source is an excellent resource for computational linguists, software engineers, IT managers, computer scientists, students and faculty of higher education, libraries, researchers, and academicians.

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Convergence of Deep Learning and Internet of Things: Computing and Technology
by T Kavitha (Editor), G Senbagavalli (Editor), Deepika Koundal (Editor)
Publisher Finelybook 出版社: IGI Global (December 30, 2022)
Language 语言: English
pages 页数: 376 pages
ISBN-10 书号: 1668462761
ISBN-13 书号: 9781668462768

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Book Description
Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

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Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence
by Chiranji Lal Chowdhary (Editor)
Publisher Finelybook 出版社: Igi Global Engineering Science Reference (October 21, 2022)
Language 语言: English
pages 页数: 324 pages
ISBN-10 书号: 1668456745
ISBN-13 书号: 9781668456743

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Book Description
Emotional intelligence has emerged as an important area of research in the artificial intelligence field as it covers a wide range of real-life domains. Though machines may never need all the emotional skills that people need, there is evidence to suggest that machines require at least some of these skills to appear intelligent when interacting with people. To understand how deep learning-based emotional intelligence can be applied and utilized across industries, further study on its opportunities and future directions is required. Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence explores artificial intelligence applications, such as machine and deep learning, in emotional intelligence and examines their use towards attaining emotional intelligence acceleration and augmentation. It provides research on tools used to simplify and streamline the formation of deep learning for system architects and designers. Covering topics such as data analytics, deep learning, knowledge management, and virtual emotional intelligence, this reference work is ideal for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

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