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Название: Mathematics for Digital Science, Volume 1: Fundamentals
Автор: Gérard-Michel Cochard, Mhand Hifi
Издательство: Wiley-ISTE
Год: 2025
Страниц: 351
Язык: английский
Формат: pdf (true), epub
Размер: 36.2 MB

Over the past century, advancements in Computer Science have consistently resulted from extensive mathematical work. Even today, innovations in the digital domain continue to be grounded in a strong mathematical foundation. To succeed in this profession, both today's students and tomorrow’s computer engineers need a solid mathematical background. The goal of this book series is to offer a solid foundation of the knowledge essential to working in the digital sector. Across three volumes, it explores fundamental principles, digital information, data analysis, and optimization. Whether the reader is pursuing initial training or looking to deepen their expertise, the Mathematics for Digital Science series revisits familiar concepts, helping them refresh and expand their knowledge while also introducing equally essential, newer topics. Today, areas such as Artificial Intelligence, managing large datasets, and information security are at the heart of Computer Science research. Once again, it is evident that without a solid mathematical foundation, it is difficult to innovate in these areas.

Название: Multimodal Data Fusion for Bioinformatics Artificial Intelligence
Автор: Umesh Kumar Lilhore, Abhishek Kumar, Narayan Vyas, Sarita Simaiya
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 396
Язык: английский
Формат: pdf (true)
Размер: 16.3 MB

Multimodal Data Fusion for Bioinformatics Artificial Intelligence is a must-have for anyone interested in the intersection of AI and bioinformatics, as it delves into innovative data fusion methods and their applications in ‘omics’ research while addressing the ethical implications and future developments shaping the field today. Multimodal Data Fusion for Bioinformatics Artificial Intelligence is an indispensable resource for those exploring how cutting-edge data fusion methods interact with the rapidly developing field of bioinformatics. Beginning with the basics of integrating different data types, this book delves into the use of AI for processing and understanding complex “omics” data, ranging from genomics to metabolomics. The revolutionary potential of AI techniques in bioinformatics is thoroughly explored, including the use of neural networks, graph-based algorithms, single-cell RNA sequencing, and other cutting-edge topics. The second half of the book focuses on the ethical and practical implications of using AI in bioinformatics. The applications of Machine Learning are gaining popularity in various fields day by day. Bioinformatics is one of the fields in which automated Machine Learning, AutoML, has great potential in the future. AutoML can be used to create the predictive models and find certain patterns in biological data.

Название: Beginning Python 3 with Claude 3
Автор: O. Campesato
Издательство: Mercury Learning and Information
Год: 2025
Страниц: 270
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 10.1 MB

This book is a comprehensive guide designed to teach the fundamentals of Python programming while introducing the exciting possibilities of Generative AI. Whether you're a novice or a developer looking to integrate Claude 3 into your workflow, this book offers a clear, step-by-step path to mastering Python and leveraging AI-driven code generation. It begins by covering Python fundamentals, including data types, string manipulation, loops, conditional logic, and exception handling. It then introduces Python collections, such as lists, dictionaries, and sets, along with their practical applications. Readers will explore essential Python libraries like NumPy and Pandas, learning how to manipulate data and perform advanced operations. The last two chapters cover Generative AI and Claude, distinguishing it from conversational AI and provides hands-on examples of Claude-generated Python code to solve various programming tasks. In essence, this book provides a modest bridge between the worlds of Python programming and AI, aiming to equip readers with the knowledge and skills to navigate both domains confidently.

Название: Generative AI for Financial Services: Challenges, anti-patterns, and best practices
Автор: Vikesh Pandey, Arnav Khare
Издательство: BPB Publications
Год: 2025
Страниц: 316
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Generative AI for Financial Services is a book targeted at any AI practitioner who wants to understand how Generative AI works on a fundamental level and extend that learning to risks, challenges, and opportunities in regulated industries like financial services. This book explores Generative AI and its applications in financial services. It starts by explaining key concepts, differences from traditional AI, and the Generative AI lifecycle. Readers learn about foundation models, transfer learning, and implementation strategies, including fine-tuning and training models. Practical use cases like improving customer experiences, automating ESG analysis, and optimizing contact centers are covered. The book also addresses challenges like model bias, ethics, and compliance while focusing on building trustworthy AI with fairness and accountability. Finally, it highlights MLOps and FMOps for efficient AI model deployment and management in production environments. The code samples given in the book are all Python based, so we expect the readers to have a basic level of understanding of Python programming language.

Название: Python for Bioinformatics: Using machine learning for drug discovery, cluster analysis, and phylogenetics
Автор: Parul Verma, Shahnaz Fatima
Издательство: BPB Publications
Год: 2025
Страниц: 256
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Python for Bioinformatics is an essential resource for anyone looking to integrate programming into their biological research. As the field of bioinformatics continues to expand, the ability to analyze vast amounts of biological data becomes increasingly crucial. This book introduces bioinformatics, blending Python programming with biological data analysis. It covers essentials like string handling, regular expressions, file I/O, and object-oriented programming. You will explore Biopython for sequence alignment, format parsing, and accessing biological databases. Learn data visualization with Matplotlib and apply bioinformatics techniques like sequence alignment and phylogenetic analysis. The final chapter includes hands-on mini-projects to solidify your understanding, making it a practical guide for mastering bioinformatics and Python in real-world applications. This book is ideal for students, researchers, and professionals in fields like biology, Computer Science, and biotechnology who seek to understand and apply bioinformatics techniques to analyze biological data and solve real-world problems.

Название: Methods and Applications of Artificial Intelligence: Dynamic Response, Learning, Random Forest, Linear Regression, Interoperability, Additive Manufacturing and Mechatronics, Volume 2
Автор: Abdelkhalak El Hami
Издательство: Wiley-ISTE
Год: 2025
Страниц: 245
Язык: английский
Формат: pdf (true)
Размер: 21.4 MB

Artificial Intelligence (AI) is currently one of the most talked-about technologies, both among scientists and in public media. Several factors have contributed to its development in recent years. The first is access to vast quantities of data, such as in the industrial field, the advent of Industry 4.0, which promotes automation and data sharing in several technologies. Another factor is the continuous improvement in computing power thanks to the development of ever more powerful processors and the optimization of algorithms. With these two limitations removed, the focus of most AI developments is on the quality of predictions. The integration of AI into the industrial domain represents an exciting new frontier for innovation. A significant number of advances in the field of AI rely on Machine Learning, an essential branch of this field. Machine Learning involves the development of algorithms and computer models that can learn from data. Unlike standard programs that follow strict instructions defined by programmers, Machine Learning systems can analyze data, detect diagrams and consequently adjust their behavior, while adapting to new information. AI and Machine Learning are closely interrelated.

Название: Essentials of R for Data Analytics
Автор: Saroj Dahiya Ratnoo, Himmat Singh Ratnoo
Издательство: Wiley
Год: 2021
Страниц: 620
Язык: английский
Формат: epub (true)
Размер: 13.1 MB

With widespread and exponential growth of data, people with Data Science background are in great demand. Data analytics, a subdomain of Data Science, is meant to turn data into insight and actionable knowledge. Data analytics mainly deals with exploring, visualizing, transforming and modelling data for making predictions. Learning R is an essential step towards becoming a data analyst. R is a widely used open-source tool that competes with the other commercially available statistical software. Be it simple data exploration or application of sophisticated statistical and data analytic techniques, the versatility of R is making it an essential tool for working with data. Data Science and data analytics are emerging as essential and much sought after skills in the world today. To be able to realise the full potential of R, it is important to have some level of expertise in R programming so that exasperation does not set in. With no or little knowledge of R programming, any straight away jumping to data analytics may lead to a loss of time and energy in finding and resolving the errors. This book is for undergraduate and postgraduate students, and for research scholars who wish to learn the essential elements of R programming and its tools for data analytics.

Название: Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes
Автор: Pethuru Raj Chelliah, Pushan Kumar Dutta, Abhishek Kumar, Ernesto D.R. Santibanez Gonzalez
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 482
Язык: английский
Формат: pdf (true)
Размер: 42.9 MB

This comprehensive volume delves deep into the diverse applications and implications of Generative AI (GenAI) across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing Generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. For writing Machine Learning code using Python various libraries like Pandas, Matplotlib, Seaborn, and ML algorithms from Sklearn. Along with the previous work conducted in the field, our study incorporates various methodologies and ML algorithms to address specific tasks such as bankruptcy detection and credit card approval prediction.

Название: React 19. Разработка веб-приложений на jаvascript
Автор: Дронов Владимир
Издательство: Bhv
Год: 2025
Формат: PDF
Страниц: 457
Размер: 39 Mb
Язык: Русский

Книга посвящена программированию веб-приложений на языке jаvascript с применением популярного веб-фреймворка React 19. В ней учтены все нововведения, появившиеся в React 19 и новых версиях сопутствующих библиотек.

Название: Python Web Scraping for Developers: Extracting Data from Websites Using Practical Python
Автор: Stephen G Schmitt
Издательство: Independently published
Год: October 7, 2024
Страниц: 149
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Python is of the most popular and versatile programming languages in the tech industry. However, despite their popularity and versatility, mastering them can be challenging, especially for beginners. Technical challenges such as debugging and tight deadlines can cause stress and anxiety, and career advancement and staying up to date with the latest developments in the field can be daunting. The process of extracting data from websites is called web scraping. Sometimes you can find it referred to as web harvesting as well. The term typically refers to an automated process that is created with intention to extract data using a bot or a web crawler. Sometimes the concept of web scraping is confused with web crawling. For this reason, we have covered this issue in our other blog post about the main differences between web crawling and web scraping. Programmers skilled in programming languages like Python can develop web data extraction scripts, so-called scraper bots. Python advantages such as diverse libraries, simplicity, and active community make it the most popular programming language for writing web scraping scripts. These scripts can scrape data in an automated way.