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Название: Data Science for Neuroimaging: An Introduction
Автор: Ariel Rokem, Tal Yarkoni
Издательство: Princeton University Press
Год: 2024
Страниц: 393
Язык: английский
Формат: pdf (true)
Размер: 12.6 MB

Data Science methods and tools―including programming, data management, visualization, and Machine Learning―and their application to neuroimaging research. As neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage, and analyze datasets at unprecedented scales. Concerns about reproducibility and increased rigor in reporting of scientific results also demand higher standards of computational practice. This book offers neuroimaging researchers an introduction to Data Science, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data. Through guided, hands-on explorations of openly available neuroimaging datasets, the book explains such elements of Data Science as programming, data management, visualization, and Machine Learning, and describes their application to neuroimaging. Readers will come away with broadly relevant Data Science skills that they can easily translate to their own questions. Note that this book is not meant to be a general introduction to programming. We are going to spend some time introducing the reader to programming in the Python programming language (starting in chapter 5; we will also explain specifically why we chose the Python programming language for this book), but for a gentler introduction to programming, we will refer you to other resources. There are a few different Python software libraries that visualize data. We will start with a library called Matplotlib.

Название: C++ Programming: A Comprehensive Beginner's Guide to Designing, Developing, and Implementing a Strong Program Through Step-by-Step Instructions
Автор: Ryan Roffe
Издательство: Independently published
Год: 2024
Страниц: 295
Язык: английский
Формат: epub (true)
Размер: 12.9 MB

Are you seeking to develop and implement a program using C++? Do you anticipate requiring substantial professional support to reach your objectives? Look no further than this book! C++ programming offers practical techniques for successfully crafting a program that endures over time. Equipped with essential design and development insights, you can swiftly grasp C++ concepts and embark on creating your own purpose-driven program. In "C++ Programming: A Comprehensive Beginner's Guide to Designing, Developing, and Implementing a Strong Program Through Step-by-Step Instructions" you'll find clear, concise information offering advantages such as: - Starting at the foundational level for immediate success; - Grasping fundamental C++ programming concepts; - Navigating across multiple devices; - Utilizing an efficient general-purpose language; - Joining a vast community of users; - Interoperability with other C languages, etc.

Название: C++ for Beginners: The Comprehensive Beginner's Handbook for Mastering C++ Programming Step-by-Step
Автор: Ryan Roffe
Издательство: Independently published
Год: 2024
Страниц: 213
Язык: английский
Формат: epub (true)
Размер: 15.8 MB

Are you faced with managing large volumes of data at work or in your hobbies? Do you seek a robust and dedicated programming language that can meet your demands? Look no further! This book serves as the ideal starting point. Packed with relevant design and development insights, you'll swiftly grasp the fundamentals of C++ and embark on crafting your own programs tailored to your needs. Its unparalleled power and adaptability render it one of the most significant languages of our era. But how does a beginner take the first steps?

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: 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.