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Название: Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data with Python's Most Popular Data Manipulation Library
Автор: Tahera Firdose
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 695
Язык: английский
Формат: pdf, epub
Размер: 22.2 MB

Unlock the power of Data Manipulation with Pandas. Unlock the power of Pandas, the essential Python library for data analysis and manipulation. This comprehensive guide takes you from the basics to advanced techniques, ensuring you master every aspect of pandas. You'll start with an introduction to pandas and data analysis, followed by in-depth explorations of pandas Series and DataFrame, the core data structures. Learn essential skills for data cleaning and filtering, and master grouping and aggregation techniques to summarize and analyze your data sets effectively. Discover how to reshape and pivot data, join and merge multiple datasets, and handle time series analysis. Enhance your data analysis with compelling visualizations using Matplotlib, and apply your knowledge in a real-world scenario by analyzing bank customer churn. Through hands-on examples and practical use cases, this book equips you with the tools to clean, filter, aggregate, reshape, merge, and visualize data effectively, transforming it into actionable insights. This book is ideal for aspiring data scientists, analysts, and Python enthusiasts looking to enhance their data manipulation skills using Pandas. Familiarity with Python programming basics and a basic understanding of data structures will greatly benefit readers as they delve into the concepts presented in this book.

Название: Расширения ядра Linux: драйверы и модули
Автор: Цилюрик О.И.
Издательство: БХВ-Петербург
Год: 2023
Страниц: 685
Язык: русский
Формат: pdf
Размер: 10.5 MB

В книге подробно рассмотрено программирование драйверов ядра Linux, исследованы возможности расширяемости ядра при помощи модулей. Основная версия ядра — 5.15. Код примеров отработан и проверен на десятках различных инсталляций Linux, установленных из различных дистрибутивов и разных семейств дистрибутивов: Fedora, CentOS, Debian, Ubuntu, Mint. Уделено внимание архитектурам x_64, x_86, ARM, а также одноплатному компьютеру Raspberry Pi и драйверам устройств, подключаемых по USB. Затронут стандарт POSIX, разобраны API ядра, работа с Raspberry Pi, системные вызовы и подключение разнообразных периферийных устройств. Эта книга рассчитана на достаточно опытных разработчиков системного программного обеспечения. Предполагается, что, возможно, у читателя и отсутствует какой-либо опыт в программировании именно для ядра Linux или даже вообще в программировании для этой системы — но предполагаются знания и какой бы то ни было опыт в системном программировании для других операционных систем, которые станут хорошей базой для построения аналогий. В высшей степени плодотворно любое знакомство с одной или несколькими POSIX-системами: Open Solaris, QNX, FreeBSD, NetBSD, MINIX3, ... — с любой из них в равной степени. Совершенно естественно, что от читателя требуется квалифицированное знание языка C — единственного необходимого и достаточного языка системного программирования в Linux. Это необходимо для самостоятельного анализа и понимания приводимых примеров — примеры приводятся, но код детально не обсуждается. Очень продуктивно в дополнение к этому (для работы с многочисленными приводимыми примерами, а еще больше — с их последующей модификацией и сравнениями) иметь хотя бы минимальные познания в языках скриптового программирования UNIX (и лучше в нескольких) — что-то из числа: bash, Perl, awk, Python...

Название: 200+ Python Programs for Beginners
Автор: Hernando Abella
Издательство: Aluna Publishing House
Серия: 200+ Programs For Beginners
Год: 2024
Страниц: 271
Язык: английский
Формат: pdf, azw3, epub (true), mobi
Размер: 10.1 MB

"The continued demand for Python skills across industries makes it a valuable asset for developers". Programming in Python was complicated until you appreciated this wonderful book. Focus on the most important thing: writing code. Starting from the first program to the last will help you quickly increase your skills as a programmer and will give you the knowledge necessary to understand: - The flow of a program; - The syntax; - The direction; - How it works; - What Add keywords to your code; - Make great decisions, and much more. This is a very essential guide with which you can learn to create more than... Once you have solved a certain number of programs, you will be able to develop yourself and turn your own ideas into a reality without even having to think about it.

Название: CodeMosaic: Learn AI-Driven Development and Modern Best Practices for Enterprise
Автор: Arpit Dwivedi
Издательство: Apress
Год: 2024
Страниц: 559
Язык: английский
Формат: pdf, epub
Размер: 24.4 MB

This book is a comprehensive guide for those navigating through the complexities of enterprise software development. For fresh graduates, transitioning from college projects to real-world applications can be overwhelming. This book acts as a roadmap, helping you bridge the gap to become industry-ready. It's like an intensive internship in book form, equipping readers with the skills and knowledge needed for modern tech roles. But it's not just for newcomers. Even experienced developers can get caught up in old routines and miss out on new tools and techniques. With the rise of AI and automation tools like ChatGPT and Copilot, the development landscape is rapidly changing. The core of the book revolves around practical application. Using .NET, Angular, and other Microsoft technologies as foundational pillars, you’ll embark on a hands-on journey. From understanding the basics to designing and deploying a full-stack web application, CodeMosaic offers a holistic learning experience. By the end, you won't just be a developer; you'll be well-equipped to tackle the challenges of today's digital world. For experienced developers looking for new tools and techniques, and recent graduates, transitioning from college projects to real-world applications.

Название: Statistical Prediction and Machine Learning
Автор: John Tuhao Chen, Lincy Y. Chen, Clement Lee
Издательство: CRC Press
Год: 2024
Страниц: 315
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Written by an experienced statistics educator and two data scientists, this book unifies conventional statistical thinking and contemporary Machine Learning framework into a single overarching umbrella over Data Science. The book is designed to bridge the knowledge gap between conventional statistics and Machine Learning. It provides an accessible approach for readers with a basic statistics background to develop a mastery of Machine Learning. The book starts with elucidating examples in Chapter 1 and fundamentals on refined optimization in Chapter 2, which are followed by common supervised learning methods such as regressions, classification, support vector machines, tree algorithms, and range regressions. After a discussion on unsupervised learning methods, it includes a chapter on unsupervised learning and a chapter on statistical learning with data sequentially or simultaneously from multiple resources. When addressing practical problems such as high dimensional inference, Machine Learning often relies on computer intensive algorithms. Many of the underlying thought processes and methodologies have been well-developed but are still fundamentally based in the conventional data analysis framework. One of the major challenges underpinning modern Machine Learning stems from the gap between the conventional model-based inference and data-driven learning algorithms. The knowledge gap hinders practitioners (especially students, researchers, data analysts, or consultants) from truly mastering and correctly applying Machine Learning skills in Data Science. This book is addressed to practitioners in Data Science, but it is also suitable for upper-level undergraduate students and entry-level graduate students who are interested in obtaining a more thorough comprehension of Machine Learning.

Название: Applied Text Mining
Автор: Usman Qamar, Muhammad Summair Raza
Издательство: Springer
Год: 2024
Страниц: 505
Язык: английский
Формат: pdf (true)
Размер: 12.9 MB

This textbook covers the concepts, theories, and implementations of text mining and Natural Language Processing (NLP). It covers both the theory and the practical implementation, and every concept is explained with simple and easy-to-understand examples. It consists of three parts. In Part 1 which consists of three chapters details about basic concepts and applications of text mining are provided, including eg sentiment analysis and opinion mining. It builds a strong foundation for the reader in order to understand the remaining parts. In the five chapters of Part 2, all the core concepts of text analytics like feature engineering, text classification, text clustering, text summarization, topic mapping, and text visualization are covered. Finally, in Part 3 there are three chapters covering deep-learning-based text mining, which is the dominating method applied to practically all text mining tasks nowadays. Various Deep Learning approaches to text mining are covered, includingmodels for processing and parsing text, for lexical analysis, and for machine translation. All three parts include large parts of Python code that shows the implementation of the described concepts and approaches. The textbook was specifically written to enable the teaching of both basic and advanced concepts from one single book. The implementation of every text mining task is carefully explained, based Python as the programming language and Spacy and NLTK as Natural Language Processing libraries. No prior knowledge of Python, Spacy, and NLTK is required. The book is suitable for both undergraduate and graduate students in Computer Science and engineering, who wish to study and learn more on this important active discipline that is considered an important milestone in Artificial Intelligence (AI). The book focuses in a unique style on looking at Generative AI to generate, understand, and interpret text.

Название: jаvascript for Automation 3: More Useful and Interesting Scripts
Автор: Jesse Shanks
Издательство: Aquitaine Publishing
Год: 2024
Язык: английский
Формат: epub
Размер: 10.1 MB

Unlock the power of automation and enhance your productivity with "jаvascript for Automation 3: More Useful and Interesting Scripts" This collection dives into the practical applications of jаvascript for Automation (JXA) on macOS, providing you with a wealth of knowledge to streamline your workflows and tackle complex tasks effortlessly. Integrating with ChatGPT, APIs, Mac Applications, between devices are all available with scripts. Whether you're a seasoned developer or a beginner, this book offers step-by-step instructions and real-world examples to help you harness the full potential of JXA. Each chapter is packed with insightful examples and practical tips, making complex automation tasks accessible and enjoyable. Whether you're looking to streamline your workflow, enhance your coding skills, or simply explore the fascinating world of JXA programming, this book is your ultimate guide to achieving more with your Mac. Embark on your automation journey today and transform the way you work with "jаvascript for Automation 3: More Useful and Interesting Scripts."

Название: Digital Image Denoising in MATLAB
Автор: Chi-Wah Kok, Wing-Shan Tam
Издательство: Wiley-IEEEPress
Год: 2024
Страниц: 227
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Presents a review of image denoising algorithms with practical MATLAB implementation guidance. Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such as array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB, this hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book. The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions. Digital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques.

Название: FastAPI: веб-разработка на Python
Автор: Билл Любанович
Издательство: Спринт Бук
Год: 2024
Формат: pdf, epub
Размер: 28 Мб
Качество: Хорошее
Язык: Русский

FastAPI — относительно новый, но надежный фреймворк с чистым дизайном, использующий преимущества актуальных возможностей Python. Как следует из названия, FastAPI отличается высоким быстродействием и способен конкурировать в этом с аналогичными фреймворками на таких языках, как Golang. Эта практическая книга расскажет разработчикам, знакомым с Python, как FastAPI позволяет достичь большего за меньшее время и с меньшим количеством кода.

Название: Tensorflow for Quantitative Finance: Transform Financial Analysis with TensorFlow's Cutting-Edge Machine Learning Techniques (Python Libraries for Finance)
Автор: Hayden Van Der Post
Издательство: Reactive Publishing
Год: 2024
Страниц: 578
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Transform your financial analysis and modeling with "TensorFlow for Quantitative Finance," the ultimate guide for financial professionals seeking to harness the power of Machine Learning. This comprehensive book equips financial analysts, data scientists, and quantitative researchers with the tools and knowledge to apply TensorFlow's advanced capabilities to a wide range of financial applications. Explore how TensorFlow can revolutionize financial modeling, from predictive analytics to risk management and algorithmic trading. This expert-level resource provides practical, hands-on examples, detailed tutorials, and real-world case studies to help you integrate TensorFlow into your quantitative finance workflows effectively. With contributions from leading industry experts, this book offers insights into the latest advancements in financial technology and practical guidance on applying TensorFlow to solve complex financial problems. Enhance your analytical skills, make data-driven decisions, and stay competitive in the evolving financial landscape with "TensorFlow for Quantitative Finance.