Название: Deep Learning for Natural Language Processing: A Gentle Introduction
Автор: Mihai Surdeanu, Marco Antonio Valenzuela-Escarcega
Издательство: Cambridge University Press
Год: 2024
Страниц: 345
Язык: английский
Формат: pdf (true)
Размер: 83.1 MB

Deep Learning is becoming increasingly important in a technology-dominated world. However, the building of computational models that accurately represent linguistic structures is complex, as it involves an in-depth knowledge of neural networks, and the understanding of advanced mathematical concepts such as calculus and statistics. This book makes these complexities accessible to those from a humanities and social sciences background, by providing a clear introduction to Deep Learning for Natural Language Processing (NLP). It covers both theoretical and practical aspects, and assumes minimal knowledge of Machine Learning, explaining the theory behind natural language in an easy-to-read way. It includes pseudo code for the simpler algorithms discussed, and actual Python code for the more complicated architectures, using modern Deep Learning libraries such as PyTorch and Hugging Face. Providing the necessary theoretical foundation and practical tools, this book will enable readers to immediately begin building real-world, practical natural language processing systems.

Название: The Complete Developer: Master the Full Stack with TypeScript, React, Next.js, MongoDB, and Docker
Автор: Martin Krause
Издательство: No Starch Press
Год: 2024
Страниц: 344
Язык: английский
Формат: epub
Размер: 10.1 MB

A hands-on, beginner-friendly approach to developing complete web applications from the ground up, using jаvascript and its most popular frameworks, including Node.js and React.js. Whether you’ve been in the developer kitchen for decades or are just taking the plunge to do it yourself, The Complete Developer will show you how to build and implement every component of a modern stack—from scratch. You’ll go from a React-driven frontend to a fully fleshed-out backend with Mongoose, MongoDB, and a complete set of REST and GraphQL APIs, and back again through the whole Next.js stack. The book’s easy-to-follow, step-by-step recipes will teach you how to build a web server with Express.js, create custom API routes, deploy applications via self-contained microservices, and add a reactive, component-based UI. You’ll leverage command line tools and full-stack frameworks to build an application whose no-effort user management rides on GitHub logins. Covers: Docker, Express.js, jаvascript, Jest, MongoDB, Mongoose, Next.js, Node.js, OAuth, React, REST and GraphQL APIs, and TypeScript.

Название: Data Science: A First Introduction
Автор: Tiffany Timbers, Trevor Campbell, Melissa Lee
Издательство: CRC Press
Серия: Data Science Series
Год: 2022
Страниц: 443
Язык: английский
Формат: pdf (true)
Размер: 30.1 MB

Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. The text emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. All source code is available online, demonstrating the use of good reproducible project workflows. Based on educational research and active learning principles, the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The book will leave readers well-prepared for Data Science projects. The use of Jupyter notebooks for exercises immediately places the student in an environment that encourages auditability and reproducibility of analyses. The integration of Git and GitHub into the course is a key tool for teaching about collaboration and community, key concepts that are critical to Data Science. The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia’s DSCI100: Introduction to Data Science course.

Название: Analysis and Visualization of Discrete Data Using Neural Networks
Автор: Koji Koyamada
Издательство: World Scientific Publishing
Год: 2024
Страниц: 230
Язык: английский
Формат: pdf (true)
Размер: 53.9 MB

This book serves as a comprehensive step-by-step guide on data analysis and statistical analysis. It covers fundamental operations in Excel, such as table components, formula bar, and ribbon, and introduces visualization techniques and PDE derivation using Excel. It also provides an overview of Google Colab, including code and text cells, and explores visualization and Deep Learning applications. Key features of the book include topics like statistical analysis, regression analysis, optimization, correlation analysis, and neural networks. It adopts a practical approach by providing examples and step-by-step instructions for learners to apply the techniques to real-world problems. The book also highlights the strengths and features of both Excel and Google Colab, allowing learners to leverage the capabilities of each platform. The clear explanations of concepts, visual aids, and code snippets aid comprehension help learners understand the principles of data analysis and statistical analysis. Overall, this book serves as a valuable resource for professionals, researchers, and students seeking to develop skills in data analysis, regression statistics, optimization, and advanced modeling techniques using Excel, Colab, and neural networks. Google Colaboratory (Colab for short) is a free cloud service provided by Google, where you can use the Jupyter notebook and Python to analyze data and build a model for Machine Learning.

Название: Measurements and Instrumentation for Machine Vision
Автор: Oleg Sergiyenko, Wendy Flores-Fuentes
Издательство: CRC Press
Год: 2024
Страниц: 466
Язык: английский
Формат: pdf (true)
Размер: 42.3 MB

A comprehensive reference book that addresses the field of machine vision and its significance in cyber-physical systems. It explores the multidisciplinary nature of machine vision, involving electronic and mechatronic devices, Artificial Intelligence algorithms, embedded systems, control systems, robotics, interconnectivity, Data Science, and cloud computing. The book aims to provide advanced students, early career researchers, and established scholars with state-of-the-art knowledge and novel content related to the implementation of machine vision in engineering, scientific knowledge, and technological innovation. The chapters of the book delve into various topics and applications within the realm of machine vision. They cover areas such as camera and inertial measurement unit calibration, technical vision systems for human detection, design and evaluation of support systems using neural networks, UV sensing in contemporary applications, fiber Bragg grating arrays for medical diagnosis, color model creation for terrain recognition by robots, navigation systems for aircraft, object classification in infrared images, feature selection for vehicle/non-vehicle classification, visualization of sedimentation in extreme conditions, quality estimation of tea using machine vision, image dataset augmentation techniques, machine vision for astronomical images, etc. The use of current technology requires measuring essential attributes from objects, health data, dimensions of a surface and weather, to mention some. These are necessary to do breakthrough innovations in a wide range of fields. The Artificial Intelligence (AI) field is one of them. This field is aimed at the research for imitating human abilities, above all, how they learn. AI can be divided into two main branches such as Machine Learning and Deep Learning.

Название: Shared-Memory Synchronization, 2nd Edition
Автор: Michael L. Scott, Trevor Brown
Издательство: Springer
Серия: Synthesis Lectures on Computer Architecture
Год: 2024
Страниц: 251
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book offers a comprehensive survey of shared-memory synchronization, with an emphasis on “systems-level” issues. It includes sufficient coverage of architectural details to understand correctness and performance on modern multicore machines, and sufficient coverage of higher-level issues to understand how synchronization is embedded in modern programming languages. The primary intended audience for this book is “systems programmers”—the authors of operating systems, library packages, language run-time systems, concurrent data structures, and server and utility programs. Much of the discussion should also be of interest to application programmers who want to make good use of the synchronization mechanisms available to them, and to computer architects who want to understand the ramifications of their design decisions on systems-level code. This second edition, published roughly a decade after the original, has numerous small improvements throughout—clarifications, bug fixes, and references to newer work. It also incorporates two major updates. First, we have re-worked and clarified the memory model and notation used in our examples. In particular, we now employ explicit load and store operations for all accesses to shared (atomic) variables, and we have adopted the C++ convention of making such accesses fully ordered (sequentially consistent) unless otherwise noted. These conventions necessitated changes to most of our algorithmic pseudocode.

Название: Exploring the Python Library Ecosystem: A Comprehensive Guide
Автор: Kameron Hussain, Frahaan Hussain
Издательство: Sonar Publishing
Год: November 8, 2023
Страниц: 321
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

"Exploring the Python Library Ecosystem: A Comprehensive Guide" is your essential companion on a journey through the rich and diverse world of Python libraries. Whether you're a beginner looking to harness the power of Python for the first time or an experienced developer seeking to expand your toolkit, this comprehensive guide offers valuable insights and hands-on knowledge to help you make the most of Python's extensive library ecosystem. Inside this book, you'll delve into the heart of Python development, uncovering a vast array of libraries and modules that can streamline your projects, boost productivity, and supercharge your code. From data science and web development to software engineering and beyond, Python libraries play a pivotal role in nearly every aspect of modern programming. Python libraries are essential tools for developers and data scientists. They are collections of pre-written code that provide various functionalities, making it easier to perform common tasks in Python programming. These libraries save time and effort by allowing users to leverage existing code rather than starting from scratch.

Название: Computational Intelligence-based Optimization Algorithms: From Theory to Practice
Автор: Babak Zolghadr-​Asli
Издательство: CRC Press
Год: 2024
Страниц: 357
Язык: английский
Формат: pdf (true)
Размер: 32.1 MB

Computational intelligence-based optimization methods, also known as metaheuristic optimization algorithms, are a popular topic in mathematical programming. These methods have bridged the gap between various approaches and created a new school of thought to solve real-world optimization problems. In this book, we have selected some of the most effective and renowned algorithms in the literature. These algorithms are not only practical but also provide thought-provoking theoretical ideas to help readers understand how they solve optimization problems. Each chapter includes a brief review of the algorithm’s background and the fields it has been used in. Additionally, Python code is provided for all algorithms at the end of each chapter, making this book a valuable resource for beginner and intermediate programmers looking to understand these algorithms.

Название: Artificial Intelligence and Multimedia Data Engineering
Автор: Suman Kumar Swarnkar, Sapna Singh Kshatri, Virendra Kumar Swarnkar
Издательство: Bentham Science
Год: December 19, 2023
Страниц: 134
Язык: английский
Формат: pdf (true), epub
Размер: 28.8 MB

Welcome to "Artificial Intelligence and Multimedia Data Engineering Vol. 1". In this book, we embark on a captivating journey through the cutting-edge realms of Artificial Intelligence (AI) and multimedia data engineering, exploring the remarkable synergies that exist between these two rapidly evolving fields. This fusion of AI and multimedia data engineering has opened up unprecedented opportunities for innovation and has profoundly impacted various industries, making it essential for researchers, practitioners, and enthusiasts alike to stay at the forefront of this dynamic landscape. Advancements in AI, coupled with the explosive growth of multimedia data, have revolutionized the way we interact with technology and perceive the world around us. From Computer Vision and natural language processing (NLP) to Deep Learning and intelligent systems, AI has become an indispensable part of our lives, shaping our experiences in ways we could have only imagined a few decades ago. Furthermore, multimedia data, including images, videos, audio, and other sensor-generated content, has become an integral part of our digital existence, leading to the creation of a vast ocean of information that needs to be efficiently processed and harnessed.

Название: Digital Image Processing and Analysis: Computer Vision and Image Analysis, 4th Edition
Автор: Scott E Umbaugh
Издательство: CRC Press
Год: 2023
Страниц: 441
Язык: английский
Формат: pdf (true)
Размер: 69.8 MB

Computer Vision and Image Analysis, focuses on techniques and methods for image analysis and their use in the development of computer vison applications. The field is advancing at an ever increasing pace, with applications ranging from medical diagnostics to space exploration. The diversity of applications is one of the driving forces that make it such an exciting field to be involved in for the 21st century. This book presents a unique engineering approach to the practice of computer vision and image analysis, which starts by presenting a global model to help gain an understanding of the overall process, followed by a breakdown and explanation of each individual topic. Topics are presented as they become necessary for understanding the practical imaging model under study, which provides the reader with the motivation to learn about and use the tools and methods being explored. The book includes chapters on image systems and software, image analysis, edge, line and shape detection, image segmentation, feature extraction and pattern classification. Numerous examples, including over 500 color images are used to illustrate the concepts discussed. Readers can explore their own application development with any programming languages, including C/C++, MATLAB, Python, and R, and software is provided for both the Windows/C/C++ and MATLAB environments.