Название: Head First jаvascript Programming: A Learner’s Guide to Modern jаvascript, 2nd Edition (Early Release)
Автор: Eric Freeman, Elisabeth Robson
Издательство: O’Reilly Media, Inc.
Год: 2024-02-06
Язык: английский
Формат: epub
Размер: 16.5 MB

What will you learn from this book? Now in its second edition, this brain-friendly guide is your comprehensive journey into modern jаvascript, covering everything from the core language fundamentals to cutting-edge features that define jаvascript today. You'll dive into the nuances of jаvascript types and the unparalleled flexibility of its functions. You'll learn how to expertly navigate classes and objects, and you'll finally understand closures. But that's just the beginning—you'll also get hands-on with the browser's document object model (DOM), engaging with jаvascript in ways you've only imagined. You won't just be reading—you'll be playing games, solving puzzles, pondering mysteries, and interacting with jаvascript. And you'll write real code, lots of it, so you can start building your own web applications. If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. With this book, you'll learn jаvascript through a multisensory experience that engages your mind—rather than a text-heavy approach that puts you to sleep.

Название: Machine Learning for Complex and Unmanned Systems
Автор: Jose Martinez-Carranza, Everardo Inzunza-González, Enrique Efrén García-Guerrero
Издательство: CRC Press
Год: 2024
Страниц: 386
Язык: английский
Формат: pdf (true)
Размер: 25.4 MB

This book highlights applications that include Machine Learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects Machine Learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of Machine Learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems, in the areas of Artificial Intelligence (AI), cryptography, embedded hardware, electronics, the Internet of Things (IoT), and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research.

Название: Online Machine Learning: A Practical Guide with Examples in Python
Автор: Eva Bartz, Thomas Bartz-Beielstein
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2024
Страниц: 163
Язык: английский
Формат: pdf (true), epub
Размер: 19.0 MB

This book deals with the exciting, seminal topic of Online Machine Learning (OML). The content is divided into three parts: the first part looks in detail at the theoretical foundations of OML, comparing it to Batch Machine Learning (BML) and discussing what criteria should be developed for a meaningful comparison. The second part provides practical considerations, and the third part substantiates them with concrete practical applications. The book is equally suitable as a reference manual for experts dealing with OML, as a textbook for beginners who want to deal with OML, and as a scientific publication for scientists dealing with OML since it reflects the latest state of research. But it can also serve as quasi OML consulting since decision-makers and practitioners can use the explanations to tailor OML to their needs and use it for their application and ask whether the benefits of OML might outweigh the costs. Chapter 1 describes the motivation for this book and the objective. Chapter 2 gives an overview and evaluation of methods and algorithms with special focus on supervised learning. Chapter 3 describes procedures for drift detection. Updateability of OML procedures is discussed in Chap. 4. Chapter 5 explains procedures for the evaluation of OML methods. Chapter 6 deals with special requirements for OML. Possible OML applications are presented in Chap. 7 and evaluated by experts in official statistics. The availability of the algorithms in software packages, especially for R and Python, is presented in Chap. 8.

Автор: Григорьев А.
Название: Компиляторы Microsoft С 5.0 и QuickC 1.0. Серия "С для PC Программирование на языке С для персональных компьютеров"; Выпуск 0
Издательство: М:, Наука
Год: 1990
Страниц: 80
Формат: DJVU, PDF
Размер: 10 МБ
Первая книга серии "С для PC" посвящена программированию с помощью современных версий компиляторов Microsoft С и QuickC, приведены практические примеры компиляции и отладки программ, рекомендации по обнаружению часто встречающихся ошибок и их исправлению, описание стандартных моделей памяти. Для широкого круга пользователей персональных компьютеров.

Название: Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas and Scikit-Learn
Автор: Abdelaziz Testas
Издательство: Apress
Год: 2023
Страниц: 500
Язык: английский
Формат: pdf (true), epub (true), mobi
Размер: 10.1 MB

Migrate from Pandas and Scikit-learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and Machine Learning with PySpark. You will learn to translate Python code from Pandas/Scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular Machine Learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Naive Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using PySpark, the industry standard for building scalable ML data pipelines. Data scientists, data engineers, and machine learning practitioners who have some familiarity with Python, but who are new to distributed machine learning and the PySpark framework.

Название: Exploring University Mathematics with Python
Автор: Siri Chongchitnan
Издательство: Springer
Год: 2023
Страниц: 521
Язык: английский
Формат: pdf (true)
Размер: 23.7 MB

This book provides a unique tour of university mathematics with the help of Python. A typical mathematics university curriculum would include some element of programming, usually in a standalone module. However, in my experience teaching at several UK universities, students often regard programming as just another module that is disparate from a typical ‘pen-and-paper’ module. In my opinion, this is an extremely unhealthy viewpoint, because programming can often help us gain a more solid understanding of mathematics in comparison to a purely pen-and-paper approach. It is true that much of university mathematics is driven by theorems and proofs, and it is also true that Python does not prove theorems. However, Python gives us the power and freedom to glimpse into the unknown, leading us towards insightful conjectures that would have been difficult to formulate otherwise. Hence, I was motivated to write a mathematics textbook that is richly interwoven with Python, rather than another Python textbook with some mathematical examples. The spirit of this book is one of mathematical exploration and investigation. I want to show students that Python can hugely enrich our understanding of mathematics through.

Название: Python – это просто. Пошаговое руководство по программированию и анализу данных
Автор: Нилаб Нисчал
Издательство: БХВ
Год: 2023
Формат: pdf
Размер: 120 Мб
Качество: Хорошее
Язык: Русский

Рассмотрены основы синтаксиса языка Python на примере дистрибутива Anaconda. Показаны приложения IPython, Spyder IDE, Jupyter Notebook. Описан синтаксис переменных, функций, циклов. Подробно изучаются структуры данных в Python: строки, списки, кортежи, множества и словари. Объясняется понятие классов и их применение в объектно-ориентированном программировании. Описаны возможности библиотеки обработки изображений Pillow, библиотеки Tkinter для создания приложений с графическим интерфейсом.

Название: Advances on Mathematical Modeling and Optimization with Its Applications
Автор: Gunjan Mukherjee, Biswadip Basu Mallik, Rahul Kar
Издательство: CRC Press
Серия: Emerging Technologies
Год: 2024
Страниц: 279
Язык: английский
Формат: pdf (true)
Размер: 22.2 MB

Advances on Mathematical Modeling and Optimization with Its Applications discusses optimization, equality, and inequality constraints and their application in the versatile optimizing domain. It further covers non-linear optimization methods such as global optimization, and gradient-based non-linear optimization, and their applications. Math has become a part of our everyday life. From the minute we wake up to the moment we go to bed, we use mathematics in every aspect of our lives. The exhaustive contribution of mathematical aspects and applicative knowledge has become research worthy due to the invention and discoveries of many advanced sorts of theorems, Whether a person is Data Scientist, Data Analyst, or Machine Learning Engineer, “Mathematics” should be a key focus of the studies. Artificial Intelligence (AI) and Machine Learning (ML) are hot topics in the computer world, and for good reason. They help companies streamline operations and unearth data so that they can make better business decisions. The business growth is directly or indirectly managed by the proper trend analysis and the predictive approach of growth to the ultimate level of development. They’re boosting almost every industry by allowing employees to work more effectively, and they’re fast becoming a critical piece of technology for businesses to remain competitive with others. Python is the most popular computer program for applying mathematical and statistical methods to AI development and applications. Therefore, we have demonstrated the applications of Python in different applications of mathematics in AI in this book.

Название: Advanced Data Fetching Patterns in React : Fast, User-Friendly Data Fetching for Developers
Автор: Juntao Qiu
Издательство: Leanpub
Год: 2024-01-27
Страниц: 105
Язык: английский
Формат: pdf (true), epub
Размер: 22.3 MB

"Advanced Data Fetching Patterns in React" is your essential guide to mastering the art of efficient data fetching in React. Discover innovative strategies and the latest features to elevate your React applications, transforming them into models of performance and efficiency. Dive in and reshape the way you handle data in your React projects! If you're developing React applications with rich API integrations, you might have noticed a trend: the more complex your app becomes, the slower and more cumbersome it feels. React's ecosystem is continually evolving, introducing many new concepts and techniques. Terms like React Server Components, Server-Side Rendering (SSR), and the Suspense API are not mere buzzwords; they represent significant shifts in how we approach building and optimizing React applications. However, mastering these advanced concepts can seem daunting. This book is your guide through the complexities of modern React development. We'll journey through the intricacies of parallel requests, lazy loading, and SSR and delve into the innovative territories of Server Components and the Suspense API. Each topic is broken down into understandable segments, providing actionable insights and clear explanations.

Автор: Касаткин В. Н.
Название: Через задачи — к программированию
Издательство: Киев. Радянська школа
Год: 1989
Страниц: 128
Формат: DJVU, PDF
Размер: 10 МБ
В книге на примере занимательных задач рассматриваются теоретические и практические основы программирования (машинного и безмашинного). Предлагаемые задачи использовались в практике работы Малой академии наук «Искатель» и полностью соответствуют интересам учащихся. При решении задач раскрываются существенные связи знакомого учащимся математического материала с важнейшими идеями программирования и основами компьютерной грамотности.