Название: Foundations of Vector Retrieval
Автор: Sebastian Bruch
Издательство: Springer
Год: 2024
Страниц: 196
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book presents the fundamentals of vector retrieval. To this end, it delves into important data structures and algorithms that have been successfully used to solve the vector retrieval problem efficiently and effectively. We are witness to a few years of remarkable developments in Artificial Intelligence (AI) with the use of advanced machine learning algorithms, and in particular, Deep Learning. Gargantuan, complex neural networks that can learn through self-supervision—and quickly so with the aid of specialized hardware—transformed the research landscape so dramatically that, overnight it seems, many fields experienced not the usual, incremental progress, but rather a leap forward. Machine translation, natural language understanding, information retrieval, recommender systems, and Computer Vision are but a few examples of research areas that have had to grapple with the shock. Countless other disciplines beyond Computer Science such as robotics, biology, and chemistry too have benefited from Deep Learning. These neural networks and their training algorithms may be complex, and the scope of their impact broad and wide, but nonetheless they are simply functions in a high-dimensional space. A trained neural network takes a vector as input, crunches and transforms it in various ways, and produces another vector, often in some other space.

Название: Java for Android Game Development: No Coding Experience? No Problem! Your Beginner's Guide to Mobile Gaming Glory
Автор: Katie Millie
Издательство: Independently published
Год: 2024
Страниц: 260
Язык: английский
Формат: pdf
Размер: 33.7 MB

Forge Your Path to Mobile Gaming Glory: Master Java for Android Game Development. Do you dream of creating the next mobile gaming phenomenon? Imagine crafting immersive worlds, designing unforgettable characters, and seeing your vision come to life on millions of devices! Java for Android Game Development is your key to unlocking this thrilling realm. This comprehensive guide is your passport to becoming a sought-after Android game developer. Within its pages, you'll gain the powerful tools and techniques of Java programming, the bedrock of building captivating games for the world's most popular mobile platform – Android. Become a Java Master: Delve into the core concepts of Java programming, from the ground up. You'll learn to control game flow, manage variables, and build robust code structures. As your skills progress, you'll be crafting real games, not just theory exercises! Unleash the Secrets of Android Game Development: Explore the intricacies of the Android development environment and essential tools. Discover how to leverage the power of Android APIs to bring your game ideas to life on various devices. No more limitations – your games will be ready for a global audience! Embrace the Power of Game Engines (Optional): Dive into the exciting world of game engines like LibGDX or Unity (with Java plugin). These powerful frameworks streamline development, allowing you to focus on creating compelling gameplay and graphics. The choice is yours: code from scratch or utilize a game engine – this book equips you with the necessary Java skills!

Название: Mastering Time Series Analysis and Forecasting with Python: Bridging Theory and Practice Through Insights, Techniques, and Tools for Effective Time Series Analysis in Python
Автор: Sulekha Aloorravi
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 310
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Decode the language of time with Python. Discover powerful techniques to analyze, forecast, and innovate. "Mastering Time Series Analysis and Forecasting with Python" is an essential handbook tailored for those seeking to harness the power of time series data in their work. The book begins with foundational concepts and seamlessly guides readers through Python libraries such as Pandas, NumPy, and Plotly for effective data manipulation, visualization, and exploration. Offering pragmatic insights, it enables adept visualization, pattern recognition, and anomaly detection. Advanced discussions cover feature engineering and a spectrum of forecasting methodologies, including Machine Learning and Deep Learning techniques such as ARIMA, LSTM, and CNN. Additionally, the book covers multivariate and multiple time series forecasting, providing readers with a comprehensive understanding of advanced modeling techniques and their applications across diverse domains.

Название: Data Analytics & Visualization All-in-One For Dummies
Автор: Jack Hyman, Luca Massaron, Paul McFedries
Издательство: For Dummies
Год: 2024
Страниц: 835
Язык: английский
Формат: pdf (true), epub (true)
Размер: 39.8 MB, 27.3 MB

Install data analytics into your brain with this comprehensive introduction. Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You'll learn all about sources of data like data lakes, and you'll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You'll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you'll be well on your way to becoming a priceless data jockey. Data Science is the person behind the partition in the experience of the wonderment of technology. Python is uniquely suited to making it easier to work with Data science. For one thing, Python provides an incredible number of math-related libraries that help you perform tasks with a less-than-perfect understanding of precisely what is going on.

Название: Enabling Microservice Success: Managing Technical, Organizational, and Cultural Challenges (Final)
Автор: Sarah Wells
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 300
Язык: английский
Формат: pdf, epub (true)
Размер: 10.1 MB

Microservices can be a very effective approach for delivering value to your organization and to your customers. If you get them right, microservices help you to move fast by making changes to small parts of your system hundreds of times a day. But if you get them wrong, microservices will just make everything more complicated. In this book, technical engineering leader Sarah Wells provides practical, in-depth advice for moving to microservices. Microservices are simple in concept, but the devil is in the details. There are so many aspects to getting the most out of this style of architecture, while also dealing with the complexity it brings. The problem is, getting the most out of microservices often is about nuance. The development of any software-based system requires people and technology coming together, and with microservices the people and organizational aspects are often greatly overlooked. People assume the answer must be a new programming language, more Kubernetes clusters, or perhaps a new vendor. But this approach results in an orgy of technological overload that ends up looking at less than half of the story.

Название: Recommender Systems: Frontiers and Practices
Автор: Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren
Издательство: Springer/House of Electronics Industry
Год: 2024
Страниц: 292
Язык: английский
Формат: pdf (true), epub
Размер: 25.0 MB

This book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of Deep Learning, focusing on the deep-learning-based technology used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it shares practical experience with Microsoft 's open source project Microsoft Recommenders. Readers can learn the design principles of recommendation algorithms using the source code provided in this book, allowing them to quickly build accurate and efficient recommender systems from scratch. The emergence of Deep Learning has greatly changed the development of recommendation technology, and it is necessary for researchers and technicians in the field of recommender systems to have a deep understanding of deep learning-based recommendation technology.

Название: LLM Adoption in the Enterprise: A Guide to Building Meaningful Products with Generative AI
Автор: Isabelle Nguyen
Издательство: O’Reilly Media, Inc.
Год: 2024-03-27
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Using large language models (LLMs) as an example, this concise guide illustrates how enterprises should approach the introduction of generative AI into their business models. From a practical understanding of the technology, to efficient and dynamic cross-functional product teams, to agile product lifecycles: packed with real-world examples, this report aims to equip thought leaders with a readily applicable framework for building with AI. Tailored copy written by a chatbot, automated code reviews, and a fully AI-driven yet empathetic and helpful customer support. The potential of large language models (LLMs) to increase productivity and drive return on investment (ROI) seems too good to be true. But this disruptive technology also presents a challenge that goes beyond cost and technical know-how. To bring an LLM-based application to production, product leaders need a pragmatic understanding of the technology, the business outcomes it can drive, and the skills required to bring their product idea to life. They must be able to lead diverse teams through the adoption process and respond to new challenges as they arise. By learning to overcome their initial awe of a new and groundbreaking technology, product leads can begin to embrace the potential of LLMs to address their users’ pain points. In this way, LLMs become a powerful addition to the product team’s toolbox that, when used properly, can solve a variety of text-based problems.

Название: jаvascript и Node.js для веб-разработчиков
Автор: Прохоренок Н.А., Дронов В.А.
Издательство: БХВ-Петербург
Год: 2022
Страниц: 767
Язык: русский
Формат: pdf
Размер: 10.3 MB

Книга рассказывает о языке программирования jаvascript, разработке на нем как программ общего назначения, выполняющихся в среде Node.js, так и скриптов для веб-страниц. Даны основы jаvascript: типы данных, операторы, работа с числами, строками, датой и временем, массивами, функции, классы (как старого, так и нового синтаксиса), итераторы, генераторы и класс Promise. Объяснена работа с отладчиком, встроенным в редактор Visual Studio Code. Рассказано о модулях, средствах для работы с файловой системой и программирования веб-серверов. Описана объектная модель документа. Рассмотрены средства для работы с элементами веб-страницы, самой страницей и браузером и технология AJAX (в том числе Fetch API), а также готовые программные пакеты для разработки веб-сайтов, в частности Webpack. С появлением Node.js появилась возможность писать на jаvascript программы практически любого назначения: инструментальные и системные утилиты, серверы и даже приложения с графическим интерфейсом (правда, для этого понадобятся дополнительные библиотеки). Предлагаемая вниманию читателей книга рассказывает о языке jаvascript, его применении для написания как программ, работающих под управлением Node.js, так и скриптов, выполняемых веб-браузерами. По сути, это всеобъемлющее руководство для jаvascript-программистов, желающих знать об этом языке все.

Название: Computational Intelligence and Blockchain in Complex Systems: System Security and Interdisciplinary Applications
Автор: Fadi Al-Turjman
Издательство: Morgan Kaufmann/Elsevier
Год: 2024
Страниц: 320
Язык: английский
Формат: epub, mobi
Размер: 11.0 MB

Computational Intelligence and Blockchain in Complex Systems: System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI, Machine Learning, and Computational Intelligence in Blockchain and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. The book examines a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and the supply chain. The authors cover the unique and developing intersection between cybersecurity and Blockchain in modern networks, as well as in-depth studies on cybersecurity challenges and multidisciplinary methods in modern Blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in Blockchain security aspects for hashing, coding, and decoding. This book provides readers with the most in-depth technical guide to the intersection of Computational Intelligence and Blockchain, two of the most important technologies for the development of next generation complex systems.

Название: Domain-Specific Computer Architectures for Emerging Applications: Machine Learning and Neural Networks
Автор: Chao Wang
Издательство: CRC Press
Год: 2024
Страниц: 417
Язык: английский
Формат: pdf (true)
Размер: 37.9 MB

With the end of Moore’s Law, domain-specific architecture (DSA) has become a crucial mode of implementing future computing architectures. This book discusses the system-level design methodology of DSAs and their applications, providing a unified design process that guarantees functionality, performance, energy efficiency, and real-time responsiveness for the target application. DSAs often start from domain-specific algorithms or applications, analyzing the characteristics of algorithmic applications, such as computation, memory access, and communication, and proposing the heterogeneous accelerator architecture suitable for that particular application. In the emerging field of big data, machine learning, data mining, and artificial intelligence algorithms, as the core components of next‑generation applications, have attracted more attention from researchers. Utilizing existing hardware and software means to carry out the design of a new algorithmic architecture has become a hot research topic nowadays. Accelerating new algorithms in the era of big data is very different from the past. Machine Learning is concerned with using data to construct appropriate predictive models to make predictions about unknown data. According to the similarity of the presentation and implementation of Machine Learning algorithms, we can categorize the algorithms such as Bayesian‑based algorithms and neural network‑based algorithms. Of course, the scope of machine learning is so vast that some algorithms are difficult to categorize explicitly into a particular class, and for some classifications, algorithms of the same classification can target different types of problems.