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Название: Balancing Automation and Human Interaction in Modern Marketing
Автор: Arjun J. Nair, Sridhar Manohar, Amit Mittal
Издательство: IGI Global
Год: 2024
Страниц: 348
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

In modern marketing, a pivotal challenge has surfaced - finding the delicate balance between automation and human interaction. This challenge stems from the rapid advancement of Artificial Intelligence (AI) technologies, which, while promising unparalleled efficiency and innovation, also lack the personal touch inherent in traditional marketing. As AI gains prominence, marketers grapple with integrating automated processes while preserving the authenticity and emotional resonance that human engagement brings. Balancing Automation and Human Interaction in Modern Marketing positions itself as a guiding force in achieving balance amid the changing marketing landscape. Within the pages of this book lies a comprehensive exploration of contemporary marketing challenges centered on striking the right balance between automation and human interaction. The quest for optimal equilibrium threads through topics such as elevating customer experiences, scalable personalization through AI, emotional intelligence in marketing, and the critical role of human-centered design. By addressing these challenges head-on, the book provides practical advice for implementing AI in marketing but positions ethics at the forefront. It advocates for responsible AI-driven marketing, fostering trust, and ensuring that the human touch remains a cornerstone of brand-consumer relationships. Designed for a diverse audience, encompassing marketers, business leaders, AI developers, educators, and consumers, the book serves as a resource for dealing with the complexities of AI-driven marketing. With recommended topics spanning from the impact of AI on customer experience to the importance of diverse perspectives in AI development, the book caters to the various interests of its readers.

Название: Computational Stochastic Programming: Models, Algorithms, and Implementation
Автор: Lewis Ntaimo
Издательство: Springer
Год: 2024
Страниц: 518
Язык: английский
Формат: pdf (true), epub
Размер: 40.5 MB

This book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their computer implementation. The book’s most important features include a focus on both risk-neutral and risk-averse models, a variety of real-life example applications of stochastic programming, decomposition algorithms, detailed illustrative numerical examples of the models and algorithms, and an emphasis on computational experimentation. With a focus on both theory and implementation of the models and algorithms for solving practical optimization problems, this monograph is suitable for readers with fundamental knowledge of linear programming, elementary analysis, probability and statistics, and some computer programming background. Several examples of stochastic programming applications areincluded, providing numerical examples to illustrate the models and algorithms for both stochastic linear and mixed-integer programming, and showing the reader how to implement the models and algorithms using computer software.

Название: Methodologies, Frameworks, and Applications of Machine Learning
Автор: Pramod Kumar Srivastava, Ashok Kumar Yadav
Издательство: IGI Global
Год: 2024
Страниц: 315
Язык: английский
Формат: pdf (true), epub
Размер: 36.4 MB

In the ever-evolving landscape of technology, Machine Learning stands as a beacon of innovation with the potential to reshape industries and redefine our daily lives. As editors of this comprehensive reference book, Methodologies, Frameworks, and Applications of Machine Learning, we are thrilled to present a compendium that encapsulates the essence of the latest advancements, theoretical foundations, and practical applications in the realm of Machine Learning. Technology is constantly evolving, and Machine Learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest Machine Learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine Learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. The Chapter 2 focuses on practical implementations of Machine Learning projects using Scikit-learn and TensorFlow libraries in Python. Four distinct projects unfold, each addressing classification, regression, and image classification problems. The step-by-step walkthrough covers model evaluation using classical Machine Learning techniques and deep neural networks.

Название: Writing AI Prompts For Dummies
Автор: Stephanie Diamond
Издательство: For Dummies
Год: 2024
Страниц: 288
Язык: английский
Формат: pdf, epub (true)
Размер: 10.3 MB

Learn the art of writing effective AI prompts and break into an exciting new career field. Unlock the full power of generative AI with Writing AI Prompts For Dummies, a comprehensive guide that will teach you how to confidentially write effective AI prompts. Whether it's text, images, or even videos and music you're aiming to create, this book provides the foundational knowledge and practical strategies needed to produce impressive results. Artificial Intelligence (AI) is revolutionizing the way we live and work at an astonishing rate. Whether you’re a marketer who wants to use AI to enhance brand awareness, a content creator who wants to improve your portfolio, or just someone curious about AI, you need to start by learning how to develop effective AI prompts. Prompts are specific instructions given to an AI tool by a user to get a particular response. This resource is brimming with expert guidance and will help you write AI prompts that achieve your objectives. Whether you're a marketer, educator, artist, or entrepreneur, Writing AI Prompts For Dummies is your indispensable guide for leveraging AI to its fullest potential. Get ready to harness the power of Artificial Intelligence and spark a revolution in your creative and professional efforts.

Название: Terraform. Инфраструктура на уровне кода
Автор: Брикман Евгений
Издательство: Спринт Бук
Год: 2024
Формат: pdf
Размер: 10 Мб
Качество: Хорошее
Язык: Русский

Terraform — настоящая звезда в мире DevOps. Эта технология позволяет управлять облачной инфраструктурой как кодом (IaC) на облачных платформах и платформах виртуализации, включая AWS, Azure и др. Третье издание было полностью переработано и дополнено, чтобы вы могли быстро начать работу с Terraform.
Евгений (Джим) Брикман знакомит вас с примерами кода на простом декларативном языке программирования Terraform, иллюстрирующими возможность развертывания инфраструктуры и управления ею с помощью команд.

Название: jаvascript Essentials For Dummies
Автор: Paul McFedries
Издательство: For Dummies
Год: 2024
Страниц: 192
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

The concise and digestible get-started guide to jаvascript programming. jаvascript Essentials For Dummies is your quick reference to all the core concepts about jаvascript—the dynamic scripting language that is often the final step in creating powerful websites. This no-nonsense book gets right to the point, eliminating review material, wordy explanations, and fluff. Find out all you need to know about the foundations of jаvascript, swiftly and crystal clear. Perfect for a brush-up on the basics or as an everyday desk reference on the job, this is the reliable little book you can always turn to for answers. What’s the difference between a page that does nothing and a page that seems to be always dancing? One word: jаvascript. If you want your pages to be dynamic and interactive, you need a bit of behind-the-scenes jаvascript to make it so. “But,” I hear you object, “HTML isn’t that hard to learn. jаvascript is a programming language, for crying out loud!” I hear you. I believe that if you begin with the basic syntax and rules, study tons of examples to learn how they work, and then slowly build up to more complex scripts, you can learn jаvascript programming. I predict here and now that by the time you finish this book, you’ll even be a little bit amazed at yourself and at what you can do. This book is to the point, focusing on the key topics you need to know about this popular programming language. Great for supplementing classroom learning, reviewing for a certification, or staying knowledgeable on the job.

Название: Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications
Автор: Shreyas Subramanian
Издательство: Wiley
Год: 2024
Страниц: 224
Язык: английский
Формат: epub (true)
Размер: 15.5 MB

Learn to build cost-effective apps using Large Language Models. In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning. Large language models (LLMs) have become a cornerstone of Artificial Intelligence (AI) research and applications, transforming the way we interact with technology and enabling breakthroughs in natural language processing (NLP). The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. Perfect for developers and data scientists interested in deploying foundational models, or business leaders planning to scale out their use of GenAI, Large Language Model-Based Solutions will also benefit project leaders and managers, technical support staff, and administrators with an interest or stake in the subject.

Название: Python All-in-One For Dummies, 3rd Edition
Автор: John Shovic, Alan Simpson
Издательство: For Dummies
Год: 2024
Страниц: 704
Язык: английский
Формат: epub (true)
Размер: 38.2 MB

Everything you need to know to get into Python coding, with 7 books in one. Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language. This book is a reference manual to guide you through the process of learning Python and how to use it in modern computer applications, such as data science, artificial intelligence, physical computing, and robotics. If you're looking to learn a little about a lot of exciting things, this is the book for you. It gives you an introduction to the topics that you'll need to explore more deeply. Python All-in-One For Dummies, 3rd Edition guides you through the Python language and then takes you on a tour through some cool libraries and technologies (the Raspberry Pi, robotics, AI, Data Science, and more) that all revolve around the Python language. When you work on new projects and new technologies, Python is there with a diverse number of libraries just waiting for you to use.

Название: Jetpack Compose 1.5 Essentials: Developing Android Apps with Jetpack Compose 1.5, Android Studio, and Kotlin
Автор: Neil Smyth
Издательство: Payload Media, Inc.
Год: 2024
Страниц: 636
Язык: английский
Формат: epub
Размер: 10.5 MB

This book teaches you how to build Android applications using Jetpack Compose 1.5, Android Studio Hedgehog (2023.1.1), Material Design 3, and the Kotlin programming language. The book begins with the basics by explaining how to set up an Android Studio development environment. The book also includes in-depth chapters introducing the Kotlin programming language, including data types, operators, control flow, functions, lambdas, coroutines, and object-oriented programming. If you are new to Kotlin programming, the entire book is appropriate for you. An introduction to the key concepts of Jetpack Compose and Android project architecture is followed by a guided tour of Android Studio in Compose development mode. The book also covers the creation of custom Composables and explains how functions are combined to create user interface layouts, including row, column, box, flow, pager, and list components. Other topics covered include data handling using state properties and key user interface design concepts such as modifiers, navigation bars, and user interface navigation. Additional chapters explore building your own reusable custom layout components, securing your apps with Biometric authentication, and integrating Google Maps. The book covers graphics drawing, user interface animation, transitions, Kotlin Flows, and gesture handling.

Название: Robust Machine Learning Distributed Methods for Safe AI
Автор: Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2024
Страниц: 180
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Today, Machine Learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure. This could, for example, result from hardware and software bugs, data poisoning or a malicious player controlling a subset of the machines. This book explains in simple terms what it means for a distributed Machine Learning scheme to be robust to these threats, and how to build provably robust Machine Learning algorithms. Studying the robustness of Machine Learning algorithms is a necessity given the ubiquity of these algorithms in both the private and public sectors. Accordingly, over the past few years, we have witnessed a rapid growth in the number of articles published on the robustness of distributed Machine Learning algorithms. We believe it is time to provide a clear foundation to this emerging and dynamic field. By gathering the existing knowledge and democratizing the concept of robustness, the book provides the basis for a new generation of reliable and safe Machine Learning schemes. In addition to introducing the problem of robustness in modern Machine Learning algorithms, the book will equip readers with essential skills for designing distributed learning algorithms with enhanced robustness. This book is intended for students, researchers, and practitioners interested in AI systems in general, and in Machine Learning schemes in particular. The book requires certain basic prerequisites in linear algebra, calculus, and probability. Some understanding of computer architectures and networking infrastructures would be helpful.