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Название: Python for Natural Language Processing: Programming with NumPy, Scikit-learn, Keras, and PyTorch, 3rd Edition
Автор: Pierre M. Nugues
Издательство: Springer
Год: 2024
Страниц: 536
Язык: английский
Формат: pdf (true), epub
Размер: 30.2 MB

Since the last edition of this book, progress has been astonishing in all areas of Natural Language Processing, with recent achievements in Text Generation that spurred a media interest going beyond the traditional academic circles. Text Processing has meanwhile become a mainstream industrial tool that is used, to various extents, by countless companies. As such, a revision of this book was deemed necessary to catch up with the recent breakthroughs, and the author discusses models and architectures that have been instrumental in the recent progress of Natural Language Processing.

Название: Numbers and Functions : Theory, Formulation, and Python Codes
Автор: G.R. Liu
Издательство: World Scientific Publishing
Год: 2024
Страниц: 226
Язык: английский
Формат: pdf (true)
Размер: 38.1 MB

This unique volume covers two fundamental elements of computational methods — numbers and functions. It provides an in-depth discussion of the behaviors of numbers, including both real and complex numbers. The discussion leads to the important closure properties of numbers, ensuring solution consistence and existence, and also possible failure in numerical computations in science and engineering.This text then introduces types of functions that take numbers as independent variables and produce a single number. Approaches for constructing inverse functions are also provided. Frequently used basis functions are introduced, with detailed studies on their properties and behaviors. Techniques are presented for constructing basis functions and their use in function approximation in computational methods. Taking advantage of the fast development of computer hardware and software, our discussions will largely be accompanied by computer codes, so that the concepts, theories, and formulations can be immediately demonstrated using examples with results plotted. We will use primarily Python in the first handful of volumes on more fundamental topics and possibly other suitable languages for more advanced topics. Python codes are used because they are currently, and in the foreseeable time, the most popular and easy-to-use tool. The idea is to break down all these difficult topics into simpler ones and conquere one by one immediately using the codes provided. As Python codes are provided, readers can easily see how the theory is formulated and how the solutions are obtained in terms of formulas, numbers, and graphs. Readers may also deepen their understanding via playing with codes and even further develop his/her own codes for solving other related problems. The book is written in Jupyter Notebook format, so that description of theory, formulation, derivation, and coding can all be done in a unified document.

Название: Programming Language Explorations, 2nd Edition
Автор: Ray Toal, Sage Strieker, Marco Berardini
Издательство: CRC Press
Год: 2024
Страниц: 408
Язык: английский
Формат: pdf (true)
Размер: 13.4 MB

Programming Language Explorations helps its readers gain proficiency in programming language practice and theory by presenting both example-focused, chapter-length explorations of fourteen important programming languages and detailed discussions of the major concepts transcending multiple languages. A language-by-language approach is sandwiched between an introductory chapter that motivates and lays out the major concepts of the field and a final chapter that brings together all that was learned in the middle chapters into a coherent and organized view of the field. Each of the featured languages in the middle chapters is introduced with a common trio of example programs and followed by a tour of its basic language features and coverage of interesting aspects from its type system, functional forms, scoping rules, concurrency patterns, and metaprogramming facilities. These chapters are followed by a brief tour of over 40 additional languages designed to enhance the reader’s appreciation of the breadth of the programming language landscape and to motivate further study. We’ve carefully chosen the order of languages to make a story out of the book. We start with Lua for its elegant design and relatively small but powerful feature set. jаvascript follows with similar features to Lua (such as first class functions and prototypal inheritance), while adding a host of modern features and a powerful event-driven, asynchronous programming model. As perhaps the world’s most popular language, jаvascript has influenced hundreds of successors, the most popular of which, TypeScript, comes next, along with an introduction to static types. The next two languages, Python and Ruby, are general-purpose scripting languages, in which we focus on first-class types and object-oriented programming, respectively. We then encounter Java, an extraordinarily popular language in the enterprise computing space.

Название: Professional Python: Object-Oriented Approaches to Efficient Software Development
Автор: Aria Thane
Издательство: Independently published
Год: 2024
Страниц: 240
Язык: английский
Формат: pdf, epub (true)
Размер: 10.7 MB

Embark on a transformative journey into the realm of Python programming with "Professional Python: Object-Oriented Approaches to Efficient Software Development." Tailored for the aspiring and seasoned developer alike, this book unfolds the expansive landscape of Python and its application in object-oriented programming (OOP) to sculpt software that stands the test of complexity and scale. From the foundational bricks of Python syntax to the architectural pillars of OOP, this guide walks you through each concept with clarity and depth. Object-oriented programming is not merely a programming paradigm; it's a way of thinking, a methodology that, when leveraged correctly, can lead to robust software design. This book is an endeavor to bridge this gap, to move beyond the basics of Python, and delve into the hows and whys of OOP, presenting it not just as a set of concepts, but as a toolkit for solving real-world software development challenges. Professional Python is crafted for a wide audience, from intermediate Python programmers who have grasped the fundamentals and are ready to dive deeper, to seasoned developers looking to refine and structure their understanding of OOP in Python. It assumes familiarity with Python's syntax and basic programming concepts, making it an ideal next step for those who wish to consolidate their skills and explore the application of OOP principles in Python to their projects. Educators and students will also find this book a valuable resource, offering a structured curriculum for teaching and learning Python's OOP features, complemented by examples, exercises, and real-world case studies. Furthermore, professionals transitioning to Python from other programming languages can leverage this book to fast-track their understanding of Pythonic OOP.

Название: Bayesian Machine Learning in Geotechnical Site Characterization
Автор: Jianye Ching
Издательство: CRC Press
Год: 2025
Страниц: 189
Язык: английский
Формат: pdf (true)
Размер: 27.1 MB

Bayesian data analysis and modelling linked with Machine Learning (ML) offers a new tool for handling geotechnical data. This book presents recent advancements made by the author in the area of probabilistic geotechnical site characterization. Two types of correlation play central roles in geotechnical site characterization: cross-correlation among soil properties and spatial-correlation in the underground space. The book starts with the introduction of Bayesian notion of probability “degree of belief”, showing that well-known probability axioms can be obtained by Boolean logic and the definition of plausibility function without the use of the notion “relative frequency”. It then reviews probability theories and useful probability models for cross-correlation and spatial correlation. Methods for Bayesian parameter estimation and prediction are also presented, and the use of these methods demonstrated with geotechnical site characterization examples. Bayesian Machine Learning in Geotechnical Site Characterization suits consulting engineers and graduate students in the area.

Название: Graphic Guide to R: with Processing.R 4 (Graphic Guide to Programming)
Автор: Antony Lees
Издательство: Devoniant
Год: 2024
Страниц: 424
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Ditch the text, unleash the graphic genius! This book is your key to mastering R through the captivating world of data visualization. With Processing's user-friendly interface, you'll be drawing shapes, animating scenes, and creating interactive experiences – all while mastering the power of R. Forget dry syntax; here, you'll grasp core concepts like variables, loops, and functions by bringing your ideas to life on the screen. Processing is a free, open-source, programming language based on the much larger R language. It focusses on the visual output of computer programs, designed for non-programmers, and those more experienced, to create visual graphics and animation. Processing includes everything needed to create and view graphics including an IDE (Integrated Development Environment) that can be used to create programs and graphics. Programming languages are often taught using text output like printing “Hello world!”. By using Processing, we can learn R with interesting graphics, giving immediate visual responses to the code you write, which is much more exciting! The book aims to teach the R programming language to both non-programmers and experienced programmers alike, allowing those who have not worked on computer programs before to become competent in the language and anyone to create some visually stunning graphics and animation using Processing, regardless of prior experience. You will soon discover that there are no real rules to creating graphics in Processing and that minor changes can yield unexpected results.

Название: Automating API Delivery: APIOps with OpenAPI (Final)
Автор: Ikenna Nwaiwu
Издательство: Manning Publications
Год: 2024
Страниц: 582
Язык: английский
Формат: epub
Размер: 18.9 MB

Improve speed, quality, AND cost by automating your API delivery process! Automating API Delivery shows you how to strike the perfect balance between speed and usability by applying DevOps automation principles to your API design and delivery process. It lays out a clear path to making both the organizational and technical changes you need to deliver high-quality APIs both rapidly and reliably. Author Ikenna Nwaiwu provides comprehensive guidance on implementing APIOps in your organization. He carefully walks through the technical steps and introduces the essential open-source tools, with practical advice and insights from his years of experience. You’ll benefit from his personal tips for avoiding common pitfalls and challenges of moving to automated API delivery. Create high quality, consistent, and fast-to-market APIs by automating the development process! This innovative book shows you how to apply established Continuous Delivery and DevOps principles along the whole API lifecycle, transforming a collection of individual tasks into a smooth, manageable pipeline that supports automated testing, iterative improvement, and reliable documentation. Automating API Delivery introduces the tools and strategies behind APIOps. You’ll discover tools and process improvements that give you important quick wins, including API governance using the Spectral API linter and establishing an efficient CI/CD pipeline with GitHub Actions. You’ll even discover how to use the powerful OpenAPI Generator to automatically create client and server code from your API definitions.

Название: Graphic Guide to Python: with Processing.py 3 (Graphic Guide to Programming)
Автор: Antony Lees
Издательство: Devoniant
Год: 2024
Страниц: 411
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Unleash Your Coding Creativity: Learn Python Through Stunning Visuals. Tired of staring at lines of text? This book is your gateway to learning Python through the magic of graphics! With Processing's user-friendly interface, you'll be drawing shapes, animating scenes, and creating interactive experiences – all while mastering the power of Python. Forget dry syntax; here, you'll grasp core concepts like variables, loops, and functions by bringing your ideas to life on the screen. Processing is a free, open-source, programming language based on the much larger Python language. It focusses on the visual output of computer programs, designed for non-programmers, and those more experienced, to create visual graphics and animation. Processing includes everything needed to create and view graphics including an IDE (Integrated Development Environment) that can be used to create programs and graphics. As Python is not a visual language, it is often taught using text output like printing “Hello world!”. By using Processing, we can learn Python with interesting graphics, giving immediate visual responses to the code you write, which is much more exciting! The book aims to teach the Python programming language to both non-programmers and experienced programmers alike, allowing those who have not worked on computer programs before to become competent in the language and anyone to create some visually stunning graphics and animation using Processing, regardless of prior experience.

Название: Mastering AI: A Survival Guide to Our Superpowered Future
Автор: Jeremy Kahn
Издательство: ‎Simon & Schuster
Год: 2024
Страниц: 336
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

A Fortune magazine journalist draws on his expertise and extensive contacts among the companies and scientists at the forefront of artificial intelligence to offer dramatic predictions of AI’s impact over the next decade, from reshaping our economy and the way we work, learn, and create to unknitting our social fabric, jeopardizing our democracy, and fundamentally altering the way we think. Within the next five years, Jeremy Kahn predicts, AI will disrupt almost every industry and enterprise, with vastly increased efficiency and productivity. It will restructure the workforce, making AI copilots a must for every knowledge worker. It will revamp education, meaning children around the world can have personal, portable tutors. It will revolutionize health care, making individualized, targeted pharmaceuticals more affordable. It will compel us to reimagine how we make art, compose music, and write and publish books. The potential of generative AI to extend our skills, talents, and creativity as humans is undeniably exciting and promising. But while this new technology has a bright future, it also casts a dark and fearful shadow. AI will provoke pervasive, disruptive, potentially devastating knock-on effects. Leveraging his unrivaled access to the leaders, scientists, futurists, and others who are making AI a reality, Kahn will argue that if not carefully designed and vigilantly regulated AI will deepen income inequality, depressing wages while imposing winner-take-all markets across much of the economy. AI risks undermining democracy, as truth is overtaken by misinformation, racial bias, and harmful stereotypes. Continuing a process begun by the internet, AI will rewire our brains, likely inhibiting our ability to think critically, to remember, and even to get along with one another—unless we all take decisive action to prevent this from happening.

Название: R Programming: Statistical Data Analysis in Research
Автор: Kingsley Okoye, Samira Hosseini
Издательство: Springer
Год: 2024
Страниц: 314
Язык: английский
Формат: pdf (true)
Размер: 17.7 MB

This book is written for statisticians, data analysts, programmers, researchers, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using R object-oriented programming language and RStudio integrated development environment (IDE). R is an open-source software with a development environment (RStudio) for computing statistics and graphical displays through data manipulation, modeling, and calculation. R packages and supported libraries provide a wide range of functions for programming and analyzing of data. Unlike many of the existing statistical software, R has the added benefit of allowing the users to write more efficient codes by using command-line scripting and vectors. It has several built-in functions and libraries that are extensible and allows the users to define their own (customized) functions on how they expect the program to behave while handling the data, which can also be stored in the simple object system. Therefore, this book serves as both textbook and manual for R statistics particularly in academic research, data analytics, and computer programming targeted to help inform and guide the work of the users. It provides information about different types of statistical data analysis and methods, and the best scenarios for use of each case in R. It gives a hands-on step-by-step practical guide on how to identify and conduct the different parametric and nonparametric procedures.