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Generative modeling is one of the hottest topics in AI. Its now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models.Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, youll understand how to make your models learn more efficiently and become more creative.Discover how variational autoencoders can change facial expressions in photosBuild practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generationCreate recurrent generative models for text generation and learn how to improve the models using attentionUnderstand how generative models can help agents to accomplish tasks within a reinforcement learning settingExplore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal Generative AI, risks, and implementations with ChatGPT Plus with GPT-4, Hugging Face, and Vertex AIKey Features- Compare and contrast 20+ models (including GPT-4, BERT, and Llama 2) and multiple platforms and libraries to find the right solution for your project- Apply RAG with LLMs using customized texts and embeddings- Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases- Purchase of the print or Kindle book includes a free eBook in PDF formatBook DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, applications, and various platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV).The book guides you through different transformer architectures to the latest Foundation Models and Generative AI. You'll pretrain and fine-tune LLMs and work through different use cases, from summarization to implementing question-answering systems with embedding-based search techniques. You will also learn the risks of LLMs, from hallucinations and memorization to privacy, and how to mitigate such risks using moderation models with rule and knowledge bases. You'll implement Retrieval Augmented Generation (RAG) with LLMs to improve the accuracy of your models and gain greater control over LLM outputs.Dive into generative vision transformers and multimodal model architectures and build applications, such as image and video-to-text classifiers. Go further by combining different models and platforms and learning about AI agent replication.This book provides you with an understanding of transformer architectures, pretraining, fine-tuning, LLM use cases, and best practices.What you will learn- Breakdown and understand the architectures of the Original Transformer, BERT, GPT models, T5, PaLM, ViT, CLIP, and DALL-E- Fine-tune BERT, GPT, and PaLM 2 models- Learn about different tokenizers and the best practices for preprocessing language data- Pretrain a RoBERTa model from scratch- Implement retrieval augmented generation and rules bases to mitigate hallucinations- Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP- Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4VWho this book is forThis book is ideal for NLP and CV engineers, software developers, data scientists, machine learning engineers, and technical leaders looking to advance their LLMs and generative AI skills or explore the latest trends in the field.Knowledge of Python and machine learning concepts is required to fully understand the use cases and code examples. However, with examples using LLM user interfaces, prompt engineering, and no-code model building, this book is great for anyone curious about the AI revolution.Table of Contents- What are Transformers?- Getting Started with the Architecture of the Transformer Model- Emergent vs Downstream Tasks: The Unseen Depths of Transformers- Advancements in Translations with Google Trax, Google Translate, and Gemini- Diving into Fine-Tuning through BERT- Pretraining a Transformer from Scratch through RoBERTa- The Generative AI Revolution with ChatGPT- Fine-Tuning OpenAI GPT Models- Shattering the Black Box with Interpretable Tools- Investigating the Role of Tokenizers in Shaping Transformer Models(N.B. Please use the Read Sample option to see further chapters)

Trustworthy AI in Medical Imaging brings together scientific researchers, medical experts, and industry partners working in the field of trustworthiness, bridging the gap between AI research and concrete medical applications and making it a learning resource for undergraduates, masters students, and researchers in AI for medical imaging applications. The book will help readers acquire the basic notions of AI trustworthiness and understand its concrete application in medical imaging, identify pain points and solutions to enhance trustworthiness in medical imaging applications, understand current limitations and perspectives of trustworthy AI in medical imaging, and identify novel research directions. Although the problem of trustworthiness in AI is actively researched in different disciplines, the adoption and implementation of trustworthy AI principles in real-world scenarios is still at its infancy. This is particularly true in medical imaging where guidelines and standards for trustworthiness are critical for the successful deployment in clinical practice. After setting out the technical and clinical challenges of AI trustworthiness, the book gives a concise overview of the basic concepts before presenting state-of-the-art methods for solving these challenges.

Computational Knowledge Vision: The First Footprints presents a novel, advanced framework which combines structuralized knowledge and visual models. In advanced image and visual perception studies, a visual model's understanding and reasoning ability often determines whether it works well in complex scenarios. This book presents state-of-the-art mainstream vision models for visual perception. As computer vision is one of the key gateways to artificial intelligence and a significant component of modern intelligent systems, this book delves into computer vision systems that are highly specialized and very limited in their ability to do visual reasoning and causal inference. Questions naturally arise in this arena, including (1) How can human knowledge be incorporated with visual models? (2) How does human knowledge promote the performance of visual models? To address these problems, this book proposes a new framework for computer vision-computational knowledge vision.

Federated Learning for Medical Imaging: Principles, Algorithms and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. In addition, it provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc. This is a complete resource for computer scientists and engineers as well as clinicians and medical care policymakers wanting to learn about the application of federated learning to medical imaging.

The mathematical theory of tangles, the centrepiece of the celebrated Robertson-Seymour theory of graph minors, finds precise structure in imprecise data. Assuming only basic undergraduate mathematics, this book shows how tangles can identify, relate, and structure types in data: of behaviour, political views, texts, or proteins.

Unlock the Power of AI with Our Neural Network Programming Book BundleAre you ready to embark on a journey into the exciting world of artificial intelligence? Do you dream of mastering the skills needed to create cutting-edge AI systems that can revolutionize industries and change the future? Look no further than our comprehensive book bundle, "Neural Network Programming: How to Create Modern AI Systems with Python, TensorFlow, and Keras."Why Choose Our Book Bundle?In this era of technological advancement, artificial intelligence is at the forefront of innovation. Neural networks, a subset of AI, are driving breakthroughs in fields as diverse as healthcare, finance, and autonomous vehicles. To harness the full potential of AI, you need knowledge and expertise. That's where our book bundle comes in.What You'll Gain· Book 1 - Neural Network Programming for Beginners: If you're new to AI, this book is your perfect starting point. Learn Python, TensorFlow, and Keras from scratch and build your first AI systems. Lay the foundation for a rewarding journey into AI development.· Book 2 - Advanced Neural Network Programming: Ready to take your skills to the next level? Dive deep into advanced techniques, fine-tune models, and explore real-world applications. Master the intricacies of TensorFlow and Keras to tackle complex AI challenges.· Book 3 - Neural Network Programming: Beyond the Basics: Discover the world beyond fundamentals. Explore advanced concepts and cutting-edge architectures like Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs). Be prepared to innovate in AI research and development.· Book 4 - Expert Neural Network Programming: Elevate yourself to expert status. Dive into quantum neural networks, ethical AI, model deployment, and the future of AI research. Push the boundaries of AI development with advanced Python, TensorFlow, and Keras techniques.Don't miss this opportunity to unlock the power of AI. Invest in your future today with "Neural Network Programming: How to Create Modern AI Systems with Python, TensorFlow, and Keras." Start your journey into the exciting world of artificial intelligence now!

The unique compendium covers a wide range of recent advanced contributions in Pattern Recognition and Artificial Intelligence, both in theoretical aspects and applications. It highlights the importance of Deep Learning in various domains, from acquisition to Decision Making.Written by world renowned contributors, this high-quality research works presents case studies that can potentially help them find approaches and resources to address their scientific problems.It is a useful reference text for professionals, researchers, academics and graduate students in the fields of artificial intelligence, machine learning and deep learning.

In an era dominated by the convergence of technology and human perception, the field of Image Processing and Machine Vision stands at the forefront of innovation. This book is a comprehensive exploration of this captivating domain, offering a blend of theoretical foundations, practical applications, and cutting-edge advancements.From enhancing medical diagnostics to enabling autonomous vehicles, from revolutionizing digital entertainment to aiding in environmental monitoring, image processing and machine vision have become indispensable tools in our modern world. This book is designed to serve as a guide, a reference, and an inspiration for students, researchers, and professionals seeking to unravel the mysteries of visual data analysis.Throughout these pages, we embark on a journey through the fundamental concepts of image processing, delve into the intricacies of computer vision algorithms, and witness the transformative power of machine learning techniques. With real-world examples and case studies, we illustrate how these technologies are reshaping industries and pushing the boundaries of what's possible.As we explore the chapters within, we encourage readers to embark on their own intellectual voyages, pushing the boundaries of creativity and problem-solving in the captivating realm of Image Processing and Machine Vision. Whether you are a novice eager to grasp the basics or an expert seeking the latest advancements, this book aims to be your trusted companion in the fascinating world of visual data analysis.Welcome to a world where pixels become insights, and images are transformed into knowledge. Enjoy the journey!

Introducing the Ultimate AI Book Bundle: Deep Learning, Computer Vision, Python Machine Learning, and Neural NetworksAre you ready to embark on an exhilarating journey into the world of artificial intelligence, deep learning, and computer vision? Look no further! Our carefully curated book bundle, "DEEP LEARNING: COMPUTER VISION, PYTHON MACHINE LEARNING AND NEURAL NETWORKS," offers you a comprehensive roadmap to AI mastery.BOOK 1 - DEEP LEARNING DEMYSTIFIED: A BEGINNER'S GUIDE ¿¿¿¿ Perfect for beginners, this book dismantles the complexities of deep learning. From neural networks to Python programming, you'll build a strong foundation in AI.BOOK 2 - MASTERING COMPUTER VISION WITH DEEP LEARNING ¿¿¿¿ Dive into the captivating world of computer vision. Unlock the secrets of image processing, convolutional neural networks (CNNs), and object recognition. Harness the power of visual intelligence!BOOK 3 - PYTHON MACHINE LEARNING AND NEURAL NETWORKS: FROM NOVICE TO PRO ¿¿¿¿ Elevate your skills with this intermediate volume. Delve into data preprocessing, supervised and unsupervised learning, and become proficient in training neural networks.BOOK 4 - ADVANCED DEEP LEARNING: CUTTING-EDGE TECHNIQUES AND APPLICATIONS ¿¿¿¿ Ready to conquer advanced techniques? Learn optimization strategies, tackle common deep learning challenges, and explore real-world applications shaping the future.Click "Add to Cart" now and embark on an educational adventure that will redefine your understanding of artificial intelligence. Your journey to AI excellence begins here!

This book offers an overview of the field of continuous biometric authentication systems, which capture and continuously authenticate biometrics from user devices. This book first covers the traditional methods of user authentication and discusses how such techniques have become cumbersome in the world of mobile devices and short usage sessions. The concept of continuous biometric authentication systems is introduced and their construction is discussed. The different biometrics that these systems may utilise (e.g.: touchscreen-gesture interactions) are described and relevant studies surveyed. It also surveys important considerations and challenges.This book brings together a wide variety of key motivations, components and advantages of continuous biometric authentication systems. The overview is kept high level, so as not to limit the scope to any single device, biometric trait, use-case, or scenario. Therefore, the contents of this book are applicable todevices ranging from smartphones to desktop computers, utilising biometrics ranging from face recognition to keystroke dynamics. It also provides metrics from a variety of existing systems such that users can identify the advantages and disadvantages of different approaches.This book targets researchers and lecturers working in authentication, as well as advanced-level students in computer science interested in this field. The book will also be of interest to technical professionals working in cyber security.

This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by ¿family¿ to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers.

This book constitutes the proceedings of the 17th Chinese Conference, CCBR 2023, held in Xuzhou, China, during December 1¿3, 2023.The 41 full papers included in this volume were carefully reviewed and selected from 79 submissions. The volume is divided in topical sections named: Fingerprint, Palmprint and Vein Recognition; Face Detection, Recognition and Tracking; Affective Computing and Human-Computer Interface; Trustworthy, Privacy and Personal Data Security; Medical and Other Applications.

The LNCS volume constitutes the refereed proceedings of 10th International Conference, PReMI 2023, in Kolkata, India, in December 2023. The 91 full papers, presented together with abstracts of 6 keynote and invited talks, were carefully reviewed and selected from more than 300 submissions. The conference presents topics covering different aspects of pattern recognition and machine intelligence with real life state-of-the-art applications.

Are you ready to become an AI Hero and make positive transformation? In Become an AI Hero: A Journey Towards Inclusive Innovation, Award-Winning Talent Development Expert, Liza Wisner takes readers on a profound odyssey into the heart of the digital era, delving deep into the far-reaching influence of Artificial Intelligence (AI) and how we can harness its power with a greater focus on inclusivity. This book will equip readers with the knowledge and tools to be a catalyst for change and use AI as a potent force for good.

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning. Sofien Kaabar--financial author, trading consultant, and institutional market strategist--introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. Understand and create machine learning and deep learning models Explore the details behind reinforcement learning and see how it's used in time series Understand how to interpret performance evaluation metrics Examine technical analysis and learn how it works in financial markets Create technical indicators in Python and combine them with ML models for optimization Evaluate the models' profitability and predictability to understand their limitations and potential

This book focuses on a wide range of breakthroughs related to digital biometrics and forensics.  The authors introduce the concepts, techniques, methods, approaches and trends needed by cybersecurity specialists and educators for keeping current their biometrics and forensics knowledge. Furthermore, the book provides a glimpse of future directions where biometrics and forensics techniques, policies, applications, and theories are headed. Topics include multimodal biometrics, soft biometrics, mobile biometrics, vehicle biometrics, vehicle forensics, integrity verification of digital content, people identification, biometric-based cybercrime investigation, among others. The book is a rich collection of carefully selected and reviewed manuscripts written by diverse digital biometrics and forensics experts in the listed fields and edited by prominent biometrics and forensics researchers and specialists.

Ce livre va bien au-delà d'une simple introduction à l'IA. À travers des chapitres approfondis et captivants, vous plongerez dans la technologie de pointe et explorerez ses caractéristiques uniques ainsi que son architecture évolutive. Vous apprendrez comment contextualiser l'IA de manière avancée, exploiter la multimodalité et personnaliser l'expérience en fonction de vos besoins.Mais les aspects éthiques et sociaux ne sont pas négligés. Il vous guidera à travers l'importance de l'éthique et de la responsabilité dans l'utilisation de l'IA et vous donnera un aperçu complet des implications éthiques et sociales. Vous découvrirez comment cette avancée technologique représente un progrès dans le domaine du support virtuel avancé et comment ses nouvelles capacités influenceront votre vie quotidienne.Le livre offre un examen approfondi de l'architecture de l'IA et explique en détail les concepts tels que les réseaux neuronaux de transformation, les mécanismes d'attention, la parallélisme et l'intégration multimodale. Vous comprendrez comment cette technologie fonctionne pendant le processus d'entraînement et génère des réponses en temps réel pour garantir une utilisation éthique.Mais la véritable innovation réside dans les applications pratiques. Vous découvrirez comment cette IA peut être utilisée dans des domaines tels que le support virtuel avancé, la création de contenu, l'éducation, la santé, l'analyse de données, le divertissement, et bien d'autres. Vous apprendrez comment interagir de manière contextuelle avec cette technologie pour obtenir une proactivité intelligente et une personnalisation dynamique.De plus, le livre comprend un tutoriel en 10 étapes sur la création d'un blog avec l'aide de cette IA. De la planification à l'optimisation SEO, de la publication à l'analyse, vous serez guidé pas à pas vers le succès de votre blog.Enfin, nous abordons les défis éthiques liés à cette technologie, y compris les questions de confidentialité, de souveraineté du contenu et de biais dans les modèles linguistiques, et nous vous donnons un aperçu des solutions en cours de développement pour relever ces défis cruciaux.

Este libro es mucho más que una simple introducción a la IA. A través de capítulos profundos y atractivos, se sumergirá en la tecnología de vanguardia y explorará sus características únicas y su arquitectura en evolución. Aprenderá a contextualizar la IA de forma avanzada, a explotar la multimodalidad y a personalizar la experiencia para adaptarla a sus necesidades.Pero no se descuidan los aspectos éticos y sociales. Le guiará a través de la importancia de la ética y la responsabilidad en el uso de la IA y le dará una visión completa de las implicaciones éticas y sociales. Descubrirá cómo este avance tecnológico representa un gran avance en la asistencia virtual avanzada y cómo sus nuevas capacidades influirán en su vida cotidiana.El libro profundiza en la arquitectura de la IA y explica con detalle conceptos como las redes neuronales transformadoras, los mecanismos de atención, el paralelismo y la integración multimodal. Entenderá cómo funciona esta tecnología durante el proceso de entrenamiento y genera respuestas en tiempo real para garantizar un uso ético.Pero la verdadera innovación reside en las aplicaciones prácticas. Descubrirá cómo puede utilizarse esta IA en ámbitos como la asistencia virtual avanzada, la creación de contenidos, la educación, la sanidad, el análisis de datos, el entretenimiento y muchos otros. Aprenderá a interactuar contextualmente con esta tecnología para lograr una proactividad inteligente y una personalización dinámica.Además, el libro incluye un tutorial de 10 pasos para crear un blog con la ayuda de esta IA. Desde la planificación hasta la optimización SEO, pasando por la publicación y el análisis, te guiará paso a paso hacia el éxito de tu blog.Por último, hablaremos de los problemas éticos asociados a esta tecnología, como la confidencialidad, la soberanía de los contenidos y los sesgos de los modelos lingüísticos, y le daremos una visión general de las soluciones que se están desarrollando para afrontar estos retos cruciales.

This volume LNCS 14253 constitutes the refereed proceedings of the 14th International Conference, ICVS 2023, in Vienna, Austria, in September 2023.. The 37 full papers presented were carefully reviewed and selected from 74 submissions. The conference focuses on Humans and Hands; Medical and Health Care; Farming and Forestry; Automation and Manufacturing; Mobile Robotics and Autonomous Systems; and Performance and Robustness.

"A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence"--