Название: Hands-On Prescriptive Analytics: Optimizing Your Decision Making with Python (Final Release)
Автор: Walter R. Paczkowski
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 460
Язык: английский
Формат: epub
Размер: 16.1 MB

Business decisions in any context—operational, tactical, or strategic—can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are usually made under the proverbial cloud of uncertainty. With this practical guide, data analysts, data scientists, and business analysts will learn why and how maximizing positive consequences and minimizing negative ones requires three forms of rich information: Descriptive analytics explores the results from an action—what has already happened. Predictive analytics focuses on what could happen. The third, prescriptive analytics, informs us what should happen in the future. While all three are important for decision-makers, the primary focus of this book is on the third: prescriptive analytics. This book is intended for people involved in demand measurement and forecasting; predictive modeling; pricing analytics including elasticity estimation; customer satisfaction assessment; market and advertisement research; new product development and research; capital investment decisions; and any place where these analyses are input into major decisions at the operational, tactical, and strategic levels. This book will provide background for Prescriptive Analytics by explaining the intuition underlying analytic concepts; developing the necessary mathematical and statistical analytic principles; demonstrating concepts using Python in JupyterLab notebooks; and illustrating analytical concepts with use-cases.

Название: Flutter App Development: How to Write for IOS and Android at Once
Автор: Rap Payne
Издательство: Apress
Год: 2024
Страниц: 328
Язык: английский
Формат: pdf
Размер: 10.1 MB

Create apps for iOS and Android phones and tablets using Flutter, a Google framework that produces two outputs for a single app. Let's face it, creating iOS apps using Apple tools such as Swift and Xcode is extremely complicated. Creating Android apps with Kotlin and Android Studio is just as difficult. This book breaks down complex concepts and tasks into easily digestible segments with examples, full-color pictures, and hands-on labs with starters and solutions. As you work through the accompanying lab exercises, you'll learn the Dart programming language; the entire Flutter development toolchain; the differences between stateful and stateless widgets; and a working knowledge of the architecture of apps. You'll work with themes and styles, develop custom widgets, and even teach your app to respond to gestures like taps, swipes, and pinches. You'll also design, create, and control the layout of your app. Create tools to handle form data entry from users. And ultimately create killer multiscreen apps with navigation, menus, and tabs. Developers who have coded in jаvascript, Python, Java, C#, C++, or any similar language. Managers, product owners, and business analysts who need to understand Flutter's capabilities.

Название: Artificial Intelligence: A Systems Approach from Architecture Principles to Deployment
Автор: David R. Martinez, Bruke M. Kifle
Издательство: The MIT Press
Год: 2024
Страниц: 577
Язык: английский
Формат: pdf
Размер: 21.9 MB

The first text to take a systems engineering approach to Artificial Intelligence (AI), from architecture principles to the development and deployment of AI capabilities. Most books on Artificial Intelligence (AI) focus on a single functional building block, such as Machine Learning or human-machine teaming. Artificial Intelligence takes a more holistic approach, addressing AI from the view of systems engineering. The book centers on the people-process-technology triad that is critical to successful development of AI products and services. Development starts with an AI design, based on the AI system architecture, and culminates with successful deployment of the AI capabilities. Directed toward AI developers and operational users, this accessibly written volume of the MIT Lincoln Laboratory Series can also serve as a text for undergraduate seniors and graduate-level students and as a reference book. ML—­one of ­today’s most rapidly growing technical fields—is a branch of Artificial Intelligence (AI) focused on employing data and algorithms to extract knowledge and insights without explicit instructions. At its core, ML is all about designing algorithms and models that can learn from data without being explic­itly programmed. It is used to recognize patterns, make classifications or predictions, and even learn to perform tasks once thought to be exclusive to ­human intelligence, such as language and image understanding and generation.

Название: Artificial Intelligence based Solutions for Industrial Applications
Автор: Pooja Jha, Shalini Mahato, Prasanta K. Jana, Sudhanshu Maurya
Издательство: CRC Press
Год: 2025
Страниц: 402
Язык: английский
Формат: pdf (true), epub
Размер: 39.2 MB

Artificial Intelligence based Solutions for Industrial Applications aims to examine the utilization of Artificial Intelligence (AI) technologies to tackle difficult industrial issues and offers readers a thorough understanding of how these technologies are being employed to address intricate industrial challenges and to stimulate innovation. This book explores the fundamental principles of Artificial Intelligence (AI) and its practical use in industrial environments. This book improves understanding of core concepts, the present state of the art and real-time implementation of AI in many industrial applications. This book describes the detailed implementation of AI in the industrial sector as well as related case studies for in-depth understanding. Basic concepts, related work reviews, illustrations, empirical results, and tables are integrated within each chapter to give the readers the opportunity to gain maximum knowledge and to easily understand the methodology and results presented. This book introduces a variety of smart algorithms to help in filtering important information and to solve problems in the application domains. Application of Machine Learning and Deep Learning in the industry demonstrates the capabilities by which it may be used to solve practical problems in the 'Fourth Industrial Revolution', and it equips readers with the necessary knowledge and tools to design solutions by themselves with the help of theory and practical examples dealt with. This book is primarily written for graduate students, engineers, and academic researchers, industrial practitioners, and anyone who wants to optimize production processes, explore AI technology, or stay ahead in the industrial field. It covers the complexities of AI in industrial contexts from core basic understanding to complex implementation.

Название: Optimizing Cloud Native Java: Practical Techniques for Improving JVM Application Performance, 2nd Edition (Final Release)
Автор: Benjamin J. Evans, James Gough
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 494
Язык: английский
Формат: True EPUB (Retail Copy)
Размер: 10.1 MB

Performance tuning is an experimental science, but that doesn't mean engineers should resort to guesswork and folklore to get the job done. Yet that's often the case. With this practical book, intermediate to advanced Java technologists working with complex platforms will learn how to tune Java cloud applications for performance using a quantitative, verifiable, and repeatable approach. In response to the ubiquity of cloud computing, this updated edition of Optimizing Cloud Native Java addresses topics that are key to high performance of Java applications in the cloud. Many resources on performance tend to focus on the theory and internals of Java virtual machines, but this book discusses the low-level technical aspects within the context of performance-tuning practicalities and examines a wide range of aspects. Java performance optimization is of interest to several different groups of professionals, not just developers. As such, it is important that we provide on-ramps for people who may be coming from different backgrounds and approaching the subject with a different grounding. The sorts of jobs that our readers might do include: - Developers; - Application support and operations staff; - DevOps engineers; - Architects. Each of these groups is likely to have a different focus and take on the material, but they all share a common interest in looking after production business applications in the cloud. They will need to understand the performance behavior of both a single-JVM application and a cloud-deployed, distributed system.

Название: Learning PyTorch 2.0, Second Edition: Utilize PyTorch 2.3 and CUDA 12 to experiment neural networks and Deep Learning models
Автор: Matthew Rosch
Издательство: GitforGits
Год: 2024
Страниц: 314
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

"Learning PyTorch 2.0, Second Edition" is a fast-learning, hands-on book that emphasizes practical PyTorch scripting and efficient model development using PyTorch 2.3 and CUDA 12. This edition is centered on practical applications and presents a concise methodology for attaining proficiency in the most recent features of PyTorch. The book presents a practical program based on the fish dataset which provides step-by-step guidance through the processes of building, training and deploying neural networks, with each example prepared for immediate implementation. Given your familiarity with Machine Learning and neural networks, this book offers concise explanations of foundational topics, allowing you to proceed directly to the practical, advanced aspects of PyTorch programming. The key learnings include the design of various types of neural networks, the use of torch.compile() for performance optimization, the deployment of models using TorchServe, and the implementation of quantization for efficient inference. Furthermore, you will also learn to migrate TensorFlow models to PyTorch using the ONNX format. The book employs essential libraries, including torchvision, torchserve, tf2onnx, onnxruntime, and requests, to facilitate seamless integration of PyTorch with production environments. Regardless of whether the objective is to fine-tune models or to deploy them on a large scale, this second edition is designed to ensure maximum efficiency and speed, with practical PyTorch scripting at the forefront of each chapter.

Название: Innovations in Modern Cryptography
Автор: Brij B. Gupta, Deepak Kalra, Ammar Almomani
Издательство: IGI Global
Год: 2024
Страниц: 569
Язык: английский
Формат: pdf (true), epub
Размер: 20.3 MB

In today's interconnected digital landscape, cybersecurity threats pose significant challenges to individuals, organizations, and governments worldwide. Cyberattacks, data breaches, and malicious activities continue to escalate in sophistication and frequency, jeopardizing sensitive information, financial assets, and critical infrastructure. Amidst this escalating threat landscape, there's a pressing need for comprehensive solutions to safeguard digital assets and ensure the integrity, confidentiality, and availability of data. Traditional security measures are proving inadequate in the face of evolving cyber threats, necessitating innovative approaches to cybersecurity. Innovations in Modern Cryptography emerges as a solution to address the complex cybersecurity challenges of the digital age. This comprehensive handbook offers a deep dive into cutting-edge cryptographic techniques, algorithms, and applications that are reshaping the landscape of cybersecurity. By exploring advanced topics such as post-quantum cryptography, homomorphic encryption, and secure multi-party computation, the book equips readers with the knowledge and tools needed to mitigate cyber risks and protect sensitive data effectively.

Название: Mastering AI Game Development with Unreal: Unleash Creativity, Empower Gameplay, and Transform Player Experiences with Advanced AI Techniques in Unreal Engine
Автор: Hrishikesh Andurlekar
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 438
Язык: английский
Формат: epub (true)
Размер: 233.5 MB

Elevate your Unreal Engine skills with This Essential Guide to AI-Driven Game Development! Book DescriptionIn the rapidly evolving world of game development, integrating Artificial Intelligence (AI) into your Unreal Engine projects is no longer optional—it’s essential. Mastering AI for Unreal Engine is your definitive guide to unlocking the transformative power of AI, propelling your games beyond the ordinary and into the realm of cutting-edge, immersive experiences. Through a step-by-step approach, you will explore a wide range of AI techniques, including pathfinding, behavior trees, perception systems, and the powerful Environment Query System (EQS). Each chapter delves into the theoretical underpinnings of these AI components, followed by hands-on exercises and real-world examples that demonstrate their integration within Unreal Engine. We will learn to create intelligent, dynamic, and engaging game experiences by leveraging the power of AI. What sets this book apart is its deep dive into emerging AI frameworks like the Mass Framework, giving you a strategic edge in adopting the latest trends and technologies that are shaping the future of gaming. You’ll learn how to optimize your AI systems, enhance performance, and master debugging techniques critical for smooth, efficient development processes. Mastering AI for Unreal Engine doesn’t just teach you AI—it empowers you to innovate, create intelligent game worlds, and stand out in the fiercely competitive game development landscape.

Название: Utilizing Generative AI for Cyber Defense Strategies
Автор: Noor Zaman Jhanjhi
Издательство: IGI Global
Год: 2025
Страниц: 546
Язык: английский
Формат: pdf (true), epub
Размер: 18.9 MB

As cyber threats become increasingly sophisticated, the need for innovative defense strategies becomes urgent. Generative Artificial Intelligence (AI) offers a revolutionary approach to enhance cybersecurity. By utilizing advanced algorithms, data analysis, and Machine Learning, Generative AI can simulate complex attack scenarios, identify vulnerabilities, and develop proactive defense mechanisms while adapting to modern-day cyber-attacks. AI strengthens current organizational security while offering quick, effective responses to emerging threats. Decisive strategies are needed to integrate Generative AI into businesses defense strategies and protect organizations from attacks, secure digital data, and ensure safe business processes. Utilizing Generative AI for Cyber Defense Strategies explores the utilization of Generative AI tools in organizational cyber security and defense. Strategies for effective threat detection and mitigation are presented, with an emphasis on Deep Learning, Artificial Intelligence, and Internet of Things (IoT) technology. This book covers topics such as cyber security, threat intelligence, and behavior analysis, and is a useful resource for computer engineers, security professionals, business owners, government officials, data analysts, academicians, scientists, and researchers.

Название: The Comprehensive Guide to Machine Learning Algorithms and Techniques
Автор: Mohammed M. Ahmed
Издательство: Independently published
Год: 2024
Страниц: 240
Язык: английский
Формат: epub
Размер: 11.4 MB

Machine Learning (ML) has rapidly grown into a pivotal technology, transforming various industries by enabling data-driven decision-making and predictive analytics. As the volume and complexity of data grows, the ability to leverage sophisticated ML algorithms becomes primary for researchers, practitioners, and enthusiasts alike. This book aims to serve as a rich resource, addressing most of the algorithms, methods, and techniques used in this field. Offering insights into each method's theoretical foundations, practical applications, and strengths and weaknesses, also provides a robust framework for selecting the most appropriate technique for many projects and research endeavors. This book has provided a comprehensive overview of various Machine Learning algorithms and techniques, categorized by their primary functions such as regression, classification, clustering, optimization, and NLP. Each algorithm has been explained in terms of its main concept, purpose, use cases, mathematical background, loss function, pros and cons, and visual representation. This knowledge is crucial for selecting the right algorithm for specific problems and understanding the underlying mechanisms that drive their performance. This book is designed to help demystify the complex world of ML algorithms. By providing clear and cutting-edge explanations of each method, along with practical examples and illustrative figures, aiming to bridge the gap between practical implementation and theoretical knowledge. Whether you are working on stock price prediction, energy consumption forecasting, natural language processing (NLP), or image recognition, this guide will supply you with the knowledge needed to make informed decisions about which ML methods to utilize. The reader is invited to delve into the fascinating ML world in this book, uncover the methods, and pave the power of data to create proper solutions and drive progress in such an important domain.