Название: Machine Learning for Decision Makers: Cognitive Computing Fundamentals for Better Decision Making 2nd Edition
Автор: Раtаnjаli Каshуар
Издательство: Apress
Год: 2024
Страниц: 676
Язык: английский
Формат: pdf
Размер: 10.1 MB

This new and updated edition takes you through the details of Machine Learning to give you an understanding of cognitive computing, IoT, Big Data, AI, quantum computing, and more. The book explains how Machine Learning techniques are used to solve fundamental and complex societal and industry problems.This second edition builds upon the foundation of the first book, revises all of the chapters, and updates the research, case studies, and practical examples to bring the book up to date with changes that have occurred in Machine Learning. A new chapter on quantum computers and Machine Learning is included to prepare you for future challenges. Insights for decision makers will help you understand Machine Learning and associated technologies and make efficient, reliable, smart, and efficient business decisions. All aspects of Machine Learning are covered, ranging from algorithms to industry applications. Wherever possible, required practical guidelines and best practices related to Machine Learning and associated technologies are discussed. Also covered in this edition are hot-button topics such as ChatGPT, superposition, Quantum Machine Learning, and reinforcement learning from human feedback (RLHF) technology. Upon completing this book, you will understand Machine Learning, IoT, and cognitive computing and be prepared to cope with future challenges related to Machine Learning. Python is an interpreted and interactive object-oriented, high-level programming language. It is called a strong general-purpose programming language. Python places strong emphasis on code reliability and simplicity so that programmers can develop applications rapidly. It is a multi-paradigm programming language, which allows users to code in several different programming styles. Python is useful for scientific and Machine Learning related tasks.

Название: Advanced Applications of Generative AI and Natural Language Processing Models
Автор: Аhmеd J. Оbаid, Вhаrаt Вhushаn, Мuthmаinnаh S. РdI
Издательство: IGI Global
Год: 2024
Страниц: 505
Язык: английский
Формат: pdf (true)
Размер: 13.6 MB

The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving. Introduction to ChatGPT: The Chapter 1 provides a comprehensive overview of ChatGPT, an advanced language model that has gained significant attention in natural language processing (NLP) and Artificial Intelligence (AI). It outlines the underlying architecture, features, applications, benefits, and limitations of ChatGPT.

Название: How javascript Works: Master the Basics of javascript and Modern Web App Development
Автор: Jоnаthоn Simрsоn
Издательство: Apress
Год: 2024
Страниц: 330
Язык: английский
Формат: pdf (true), epub
Размер: 10.8 MB

javascript is a complicated language with a lot of misinformation surrounding how it works. This book provides a comprehensive introduction to javascript, from how it works at a technical level to how it is used to create websites and applications. Everything you need to know to start a career in javascript development is covered here. How javascript Works begins with a practical introduction of the basics before moving into the technical underpinnings of javascript, detailing everything you need to know, including variables, memory storage, functions, classes, types, maps, sets and APIs. Once you’ve fully absorbed these key topics. author Jonathan Simpson will show you how to put them into practice, demonstrating how they are employed for modern web development. You’ll learn how to use javascript with HTML and CSS to construct web pages and applications, how to change CSS with javascript, and how to utilize Fetch and asynchronous operations. Upon completing this book, you will have the foundational knowledge necessary to continue your journey to becoming a professional javascript developer. For anyone interested in a web development career, as well as those who may have already embarked on their careers, but who want to deepen their technical understanding of javascript and how it works.

Название: Getting Started with Containers in Azure: Deploy Secure Cloud Applications Using Terraform, 2nd Edition
Автор: Shimоn Ifrаh
Издательство: Apress
Год: 2024
Страниц: 221
Язык: английский
Формат: pdf (true), epub
Размер: 10.6 MB

Master the skills needed to deploy container services on Microsoft Azure using Terraform. This book will take you through the entire process of designing, deploying, and managing container services such as Azure Kubernetes Service (AKS), Azure Container Instances (ACI), Azure Container Registry (ACR), and Azure Web App for Containers. In this fully updated second edition, Author Shimon Ifrah demonstrates how to use Terraform, PowerShell and Azure CLI to provision and manage container services in Azure. As you’ll be using Terraform as the main tool for deployment, a basic knowledge of Terraform is a prerequisite. In addition, you will see how Azure DevOps services can be used to deploy infrastructure and container services with Terraform using Azure Pipelines without using the Azure Portal. The book concludes with a tutorial on how to use Azure Defender for Cloud to safeguard Terraform and infrastructure-as-code against malicious threats, so you can deliver secure applications. Upon completing this book, you will have a thorough understanding of how to use Terraform to deploy secure and efficient cloud applications on Azure. For Azure administrators, developers, and architects who want to get started and learn more about containers and containerized applications on Microsoft Azure.

Название: Visual Studio Extensibility Development: Extending Visual Studio IDE for Productivity, Quality, Tooling, Analysis, and Artificial Intelligence, 2nd Edition
Автор: Rishаbh Vеrmа
Издательство: Apress
Год: 2024
Страниц: 455
Язык: английский
Формат: pdf (true)
Размер: 23.0 MB

Master Visual Studio extensibility for an enhanced Visual Studio IDE experience. This book is a comprehensive guide that covers every facet of developing, debugging, and publishing extensions that amplify your productivity, tooling, and analysis within the Visual Studio IDE. This new edition is updated for Visual Studio 2022, which is the latest and greatest version of Visual Studio. Since the last edition, Artificial Intelligence (AI) has taken the world by the storm. This revised edition demonstrates how AI can take your extensions to unparalleled heights using ChatGPT. The book begins with an introduction to the essential concepts of Visual Studio, including data structures and design patterns before diving into the fundamentals of the Visual Studio extensibility model. Here you will learn the anatomy of a VSIX and how extensions are discovered and loaded in Visual Studio. Next, you will explore the extensibility model and see how various extensions, such as menus, commands, and tool windows can be plugged into Visual Studio. Moving forward, you’ll cover developing VS extensions and how they can be made configurable by customizing the UI and options page, and you’ll learn to develop a VS extension that leverages ChatGPT. Next, you will see how to extend the most often used component of Visual Studio, the code editor, before creating your own sample code snippets and templates. This is followed by a demonstration of how to deploy extensions using continuous integration (CI). Finally, you will learn tips and tricks for Visual Studio and its extensibility, along with a few highly valuable extensions. After reading Visual Studio Extensibility Development, you will be able to develop, debug, customize, and deploy extensions in Visual Studio IDE.

Название: Handbook of Research on AI and ML for Intelligent Machines and Systems
Автор: Вrij В. Guрtа, Frаnсеsсо Соlасе
Издательство: IGI Global
Год: 2024
Страниц: 530
Язык: английский
Формат: pdf (true), epub
Размер: 33.6 MB

The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by Artificial Intelligence (AI) and Machine Learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.

Название: Machine Learning Algorithms Using Scikit and TensorFlow Environments
Автор: Рuvvаdi Ваbу Маruthi, Smritу Рrаsаd, Аmit Кumаr Туаgi
Издательство: IGI Global
Год: 2024
Страниц: 473
Язык: английский
Формат: pdf (true)
Размер: 14.2 MB

Machine Learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students. Machine Learning plays a vital role in all major sectors like healthcare, banking, finance, and marketing. There is a need to understand the role and working of ML algorithms in a better way. Google also uses a learning algorithm to rank the web pages whenever we try to browse the internet to get the desired information. Understanding the platform and working of these algorithms is crucial for researchers. In the Chapter 2, the authors have presented an overview of Machine Learning fundamentals and the working of these algorithms with suitable examples. They have also highlighted the importance of major Machine Learning libraries like TensorFlow and SciKit in developing and deploying vast applications. Finally, a case study of ML application is presented to better understand the concept. Future prospects of ML applications are also depicted in detail.

Название: WAIC and WBIC with Python Stan: 100 Exercises for Building Logic
Автор: Jое Suzuki
Издательство: Springer
Год: 2023
Страниц: 249
Язык: английский
Формат: pdf (true), epub
Размер: 46.2 MB

Master the art of Machine Learning and Data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you’re a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory. It is very inconvenient if there is no source code in a Machine Learning book. Furthermore, even if there is a package, without the source code, you cannot improve the algorithm. Sometimes the source is made public on platforms like git, but it may only be available in MATLAB or Python or may not be sufficient. In this book, code is written for most processes, so you can understand what it means even if you don't understand the math. Embark on your Machine Learning and Data Science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!

Название: Python Programming for Lucrative Careers: Your Fast-Track to Mastering Python Skills in Just One Week with Insider Coding Hacks + 30 Hands-On Exercises Included
Автор: Niсhоlаs Dеmрsеу
Издательство: Independently published
Год: 2023
Страниц: 174
Язык: английский
Формат: pdf (true)
Размер: 27.3 MB

Do you dream of unlocking high-paying job opportunities and enhancing your career prospects with these in-demand skills? Are you searching for a comprehensive guide that will demystify Python, propelling you from a beginner to a coding hero? Python has become the backbone of modern computing, offering unparalleled capabilities for web development, data analysis, automation, and beyond. In just seven days, you can transition from a coding novice to a proficient programmer. Our accelerated approach optimizes your learning curve, ensuring every moment counts. Whether you're a novice or have dabbled in coding before, this book is your key to unlocking the potential of these languages without the confusion or overwhelming technicalities. Your time is invaluable, and I've distilled years of coding expertise into this comprehensive guide. Whether you're a student, a career switcher, or simply curious about the coding universe, this book is tailored for you. Don't miss this opportunity to transform your career prospects and unlock the world of high-paying tech jobs.

Название: Applied Machine Learning Using mlr3 in R
Автор: Веrnd Вisсhl, Rарhаеl Sоnаbеnd, Lаrs Коtthоff
Издательство: CRC Press
Год: 2024
Страниц: 356
Язык: английский
Формат: pdf (true)
Размер: 37.0 MB

mlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art Machine Learning capabilities in R. Applied Machine Learning Using mlr3 in R gives an overview of flexible and robust Machine Learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic Machine Learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of Machine Learning approaches to obtain peak performance; building Machine Learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with custom learners, measures, or pipeline components. The book is primarily aimed at researchers, practitioners, and graduate students who use Machine Learning or who are interested in using it. It can be used as a textbook for an introductory or advanced Machine Learning class that uses R, as a reference for people who work with Machine Learning methods, and in industry for exploratory experiments in Machine Learning.