The essential blueprints and workflow you need to build successful AI business applications Key FeaturesLearn and master the essential blueprints to program AI for real-world business applicationsGain insights into how modern AI and machine learning solve core business challengesAcquire practical techniques and a workflow that can build AI applications using state-of-the-art software librariesWork with a practical, code-based strategy for creating successful AI solutions in your businessBook Description AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You’ll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you’ll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You’ll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a ‘trending now’ section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers’ questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you’ll also learn how to prepare for future advances in AI. You’ll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. What you will learnAn essential toolbox of blueprints and advanced techniques for building AI business applicationsHow to design and deploy AI applications that meet today’s business needsA workflow from first design stages to practical code solutions in your next AI projectsSolutions for AI projects that involve social media analytics and recommendation enginesPractical projects and techniques for sentiment analysis and helpful chatbotsA blueprint for AI projects that recommend products based on customer purchasing habitsHow to prepare yourself for the next decade of AI and machine learning advancementsWho this book is for Programming AI Business Applications provides an introduction to AI with real-world examples. This book can be read and understood by programmers and students without requiring previous AI experience. The projects in this book make use of Java and Python and several popular and state-of-the-art opensource AI libraries.

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

TAGLINE Elevate your Unreal Engine skills with This Essential Guide to AI-Driven Game Development! KEY FEATURES ● Comprehensive coverage of AI techniques and their Unreal Engine implementation ● Practical hands-on exercises and real-world examples for seamless AI integration ● Covers all important AI workflows in Unreal Engine DESCRIPTION In 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. WHAT WILL YOU LEARN ● Set up and navigate Unreal Engine to establish a strong foundation for AI development. ● Learn Blueprints, create class Blueprints, and use Blueprint communication for interactive AI components. ● Build AI characters, and master navigation meshes and pathfinding for dynamic movement. ● Create complex AI behaviors using Behavior Trees and Blackboard components. ● Implement AI Perception to add sight and hearing, making your AI characters more aware and reactive. ● Use State Trees to manage AI states with evaluators, tasks, and transitions. ● Leverage the Environmental Query System (EQS) to enable AI to make context-aware decisions. ● Debug and optimize AI with Unreal’s visual logging and debugging tools. ● Explore advanced AI design techniques like Data Oriented Design, Mass AI, and ZoneGraph. WHO IS THIS BOOK FOR? This book is tailored for game developers, aspiring designers, and anyone interested in integrating AI into Unreal Engine projects. Suitable for beginners to experienced professionals, it’s ideal for students, hobbyists, and industry pros looking to enhance their AI skills. Whether you're creating Non-Player Characters (NPCs), designing complex decision-making systems, or advancing game AI, this book provides the tools and knowledge you need to succeed. TABLE OF CONTENTS 1. Introduction to Unreal Engine 2. Unreal Blueprints 3. Understanding AI in Games 4. Navigation and Pathfinding 5. Behavior Trees and Blackboards 6. AI Perception 7. StateTree 8. Environment Query System 9. SmartObjects 10. Debugging AI in Unreal Engine 11. Mass Framework and Future Trends in GameAI Index

AI + ITIL V4: The Ultimate Roadmap to Digital Transformation Excellence In the era of rapid digital evolution, businesses that do not integrate Artificial Intelligence (AI) into their processes risk falling behind. "AI + ITIL V4: The Ultimate Roadmap to Digital Transformation Excellence" is the definitive guide for organizations seeking to leverage AI while adhering to the best practices of ITIL V4. This comprehensive book offers a clear, actionable roadmap for business leaders, IT managers, and strategic professionals who want to drive innovation, improve service management, and achieve operational excellence. By blending AI technologies with the structured ITIL V4 framework, you’ll learn how to streamline your digital transformation journey with confidence. Key topics covered include: How to align AI-powered services with business goals for maximum impact. Using the ITIL V4 Service Value Chain to manage AI deployments. The role of automation, data analytics, and cloud computing in driving business agility. Real-world case studies that show the transformative power of AI in different industries. Step-by-step guidelines for implementing AI, optimizing IT services, and achieving continuous improvement. Who is this book for? This essential guide is designed for CEOs, CIOs, IT Directors, business leaders, and IT professionals seeking to transform their organizations. It’s also a vital resource for project managers and consultants involved in AI and digital transformation projects. Whether you are looking to improve operational efficiency, enhance customer experiences, or drive innovation, this book provides the tools and insights necessary for success in the digital age. Don’t miss out on the opportunity to lead your organization's transformation—read it today!

"This volume reports 16 AI projects on engineering sustainability using AI, Machine Learning, Signal Processing, Databases and other Technologies (Hybrid AI). Sixty scientists contribute to the volume on ‘Boots on the Ground’ topics including fire fighting, forestry sustainability, flood prediction, algae bloom prediction, water pollution prediction, sewage treatment, recycling and resource consumption. There are also ‘Data, Data Everywhere’ topics including biodiversity cataloguing, plant physiology and climate modeling, forest ecosystem modelling, satellite data aggregation and viewing and weather forecasting. The contributions of each team of scientists, AI researchers and engineers has been assembled with a set of helpful questions and answers called “Classroom Connection” at the end of each chapter. The existence of this book serves to document the AI projects in existence and some of the people who have been actively working to create sustainability using AI. Inside you’ll find many examples of hybrid AI - systems so complex, they need every AI trick in the book to solve them, and then some. The book is presented at the 2019 U.N. Climate Summit in Madrid Spain."--Publisher's description.

Handy Book for Generative AI in Enterprise Architecture

When it comes to understanding the potential of generative AI in the field of enterprise architecture, the possibilities are truly limitless. In this subchapter, we will explore how this technology can be leveraged to transform the way organizations approach their architectural design and decision-making processes. Generative AI, a subset of artificial intelligence, has the capability to generate novel ideas, designs, and solutions based on a given set of parameters and objectives. This can revolutionize the way organizations approach enterprise architecture, as it offers the ability to automate and optimize various aspects of the architectural process. In this subchapter, we will delve into the key concepts and principles of generative AI and its relevance to enterprise architecture. We will explore how this technology can be utilized to streamline the design and decision-making process, reduce time and resources, and ultimately enhance the overall effectiveness of an organization's architectural endeavors. Furthermore, we will discuss the various applications and use cases of generative AI in enterprise architecture. From creating intelligent blueprints to generating optimized architectural designs, this technology can assist architects and organizations in making informed decisions and developing innovative solutions. To fully grasp the potential of generative AI in enterprise architecture, it is crucial to understand the challenges and considerations associated with its implementation. We will address the potential limitations and risks of relying solely on generative AI, while also highlighting the importance of human expertise and collaboration in conjunction with this technology. Lastly, in this subchapter, we will provide practical guidance on how organizations can begin incorporating generative AI into their architectural processes. We will outline the steps and best practices required to successfully implement generative AI solutions, while also emphasizing the need for continuous learning and adaptation.

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations

This book constitutes the refereed proceedings of the 25th Australasian Joint Conference on Artificial Intelligence, AI 2012, held in Sydney, Australia, in December 2012. The 76 revised full papers presented were carefully reviewed and selected from 196 submissions. The papers address a wide range of agents, applications, computer vision, constraints and search, game playing, information retrieval, knowledge representation, machine learning, planning and scheduling, robotics and uncertainty in AI.

Tap into the cutting-edge artificial intelligence features of Unreal Engine 5 and unlock their potential to craft captivating and engaging experiences in your games and applications in this part-color guide Key Features Adopt AI techniques for developing immersive gameplay experiences Learn how to use the Unreal Engine gameplay framework system with C++ and Blueprints Plan and develop AI behaviors carefully from start to finish Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionHave you ever wondered how to create engaging gameplay experiences that involve formidable AI opponents, capable of challenging and pushing players to their limits? If the answer is yes, then get ready to enter the realm of AI creation with Unreal Engine 5. Within the pages of this book, written by a brilliant author and game development expert, you’ll find the secrets of Unreal Engine's cutting-edge AI framework. With this newfound knowledge, you’ll be able to create immersive and dynamic gaming experiences. This step-by-step guide will teach you the art of crafting intelligent and responsive virtual opponents that challenge and engage players on a whole new level. As you follow along with practical examples, the book will guide you through the creation of fully functional AI systems. You’ll be able to harness the power of behavior trees, NavMesh systems, and sensory perception models, breathing life into your virtual characters. By the end of this book, you’ll be equipped with the knowledge you need to unleash the full potential of AI in Unreal Engine. Get ready to revolutionize your gaming creations and captivate players with AI-driven wonders that push the boundaries of what's possible!What you will learn Discover the basics of AI development in video games Gain a deep understanding of the main actors in the Unreal Engine AI framework Design and develop engaging AI actors for a game Create dynamic and immersive AI experiences with behavior trees, navigation systems, MassEntity, and other AI features Debug AI systems using dedicated Unreal Engine debugging tools Extend the AI system with custom nodes and functions Understand how to cope with the AI system by employing Blueprints and/or C++ Create games that focus on tactics, motion, and more Who this book is for This book is for game programmers, as well as Unreal Engine developers with little to no knowledge of AI systems in video games, who want to explore this topic in depth. Developers who are proficient in other game engines and are interested in understanding the principles of the Unreal AI framework will also benefit from this book. You’ll need basic knowledge of Unreal Engine and C++ and a strong passion for game development to get the most out of this book.