Transformers In Deep Learning Architecture
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Transformers In Deep Learning Architecture
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-05-28
Transformers In Deep Learning Architecture written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-28 with Computers categories.
"Transformers in Deep Learning Architecture" "Transformers in Deep Learning Architecture" presents a comprehensive and rigorous exploration of the transformer paradigm—the foundational architecture that has revolutionized modern artificial intelligence. The book opens by situating transformers within the historical context of neural sequence models, methodically tracing their evolution from recurrent neural networks to the self-attention mechanisms that address their predecessor’s limitations. Early chapters lay a strong mathematical and conceptual foundation, introducing key terminology, theoretical principles, and detailed comparisons with alternative architectures to prepare readers for a deep technical dive. At its core, the book delivers an in-depth analysis of the architectural details and operational intricacies that underpin transformer models. Subsequent chapters dissect the encoder-decoder framework, decompose self-attention and multi-head attention mechanisms, and discuss design choices such as positional encodings, feedforward networks, normalization strategies, and scaling laws. Readers also encounter a nuanced treatment of advanced attention variants—including efficient, sparse, and cross-modal extensions—along with proven paradigms for pretraining, transfer learning, and domain adaptation. Rich case studies illustrate the extraordinary performance of transformers in natural language processing, vision, audio, and multimodal tasks, highlighting both established applications and emerging frontiers. Beyond technical mastery, the book addresses the practical dimensions and responsible deployment of large transformer models. It guides practitioners through scalable training, distributed modernization, and infrastructure optimization, while confronting contemporary challenges in interpretability, robustness, ethics, and privacy. The final chapters forecast the transformative future of the field with discussions on long-context modeling, symbolic integration, neuromorphic and quantum-inspired approaches, and the profound societal implications of widespread transformer adoption. Altogether, this volume stands as both an authoritative reference and a visionary roadmap for researchers and engineers working at the cutting edge of deep learning.
The Deep Learning Architect S Handbook
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Author : Ee Kin Chin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-29
The Deep Learning Architect S Handbook written by Ee Kin Chin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Computers categories.
Harness the power of deep learning to drive productivity and efficiency using this practical guide covering techniques and best practices for the entire deep learning life cycle Key Features Interpret your models’ decision-making process, ensuring transparency and trust in your AI-powered solutions Gain hands-on experience in every step of the deep learning life cycle Explore case studies and solutions for deploying DL models while addressing scalability, data drift, and ethical considerations Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDeep learning enables previously unattainable feats in automation, but extracting real-world business value from it is a daunting task. This book will teach you how to build complex deep learning models and gain intuition for structuring your data to accomplish your deep learning objectives. This deep learning book explores every aspect of the deep learning life cycle, from planning and data preparation to model deployment and governance, using real-world scenarios that will take you through creating, deploying, and managing advanced solutions. You’ll also learn how to work with image, audio, text, and video data using deep learning architectures, as well as optimize and evaluate your deep learning models objectively to address issues such as bias, fairness, adversarial attacks, and model transparency. As you progress, you’ll harness the power of AI platforms to streamline the deep learning life cycle and leverage Python libraries and frameworks such as PyTorch, ONNX, Catalyst, MLFlow, Captum, Nvidia Triton, Prometheus, and Grafana to execute efficient deep learning architectures, optimize model performance, and streamline the deployment processes. You’ll also discover the transformative potential of large language models (LLMs) for a wide array of applications. By the end of this book, you'll have mastered deep learning techniques to unlock its full potential for your endeavors.What you will learn Use neural architecture search (NAS) to automate the design of artificial neural networks (ANNs) Implement recurrent neural networks (RNNs), convolutional neural networks (CNNs), BERT, transformers, and more to build your model Deal with multi-modal data drift in a production environment Evaluate the quality and bias of your models Explore techniques to protect your model from adversarial attacks Get to grips with deploying a model with DataRobot AutoML Who this book is for This book is for deep learning practitioners, data scientists, and machine learning developers who want to explore deep learning architectures to solve complex business problems. Professionals in the broader deep learning and AI space will also benefit from the insights provided, applicable across a variety of business use cases. Working knowledge of Python programming and a basic understanding of deep learning techniques is needed to get started with this book.
Applied Machine Learning And Deep Learning Architectures And Techniques
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Author : Nitin Liladhar Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-13
Applied Machine Learning And Deep Learning Architectures And Techniques written by Nitin Liladhar Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-13 with Computers categories.
This book provides an extensive overview of recent advances in machine learning (ML) and deep learning (DL). It starts with a comprehensive introduction to the latest architectural and design practices, with an overview of basic techniques and optimization algorithms and methodologies that are fundamental to modern ML/DL development followed by the tools and frameworks that are driving innovation in ML/DL. The presentation then points to the central position of ML and DL in developing generative AI like ChatGPT. Then look at different industrial applications such as explaining the real-world impacts of each. This includes challenges around corroborate artificial Intelligence (AI), and trustworthy AI, and so on. Finally, the book presents a futuristic vision on the potentials and implications of future ML and DL architectures, making it an ideal guide for researchers, practitioners and industry professionals. This book will be a significant resource for comprehending present advancements, addressing encounter challenges, and traversing the ML and DL landscape in future, making it an indispensable reference for anyone interested in applying these technologies across sectors.
3d Data Science With Python
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Author : Florent Poux
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-04-09
3d Data Science With Python written by Florent Poux and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-09 with Computers categories.
Our physical world is grounded in three dimensions. To create technology that can reason about and interact with it, our data must be 3D too. This practical guide offers data scientists, engineers, and researchers a hands-on approach to working with 3D data using Python. From 3D reconstruction to 3D deep learning techniques, you'll learn how to extract valuable insights from massive datasets, including point clouds, voxels, 3D CAD models, meshes, images, and more. Dr. Florent Poux helps you leverage the potential of cutting-edge algorithms and spatial AI models to develop production-ready systems with a focus on automation. You'll get the 3D data science knowledge and code to: Understand core concepts and representations of 3D data Load, manipulate, analyze, and visualize 3D data using powerful Python libraries Apply advanced AI algorithms for 3D pattern recognition (supervised and unsupervised) Use 3D reconstruction techniques to generate 3D datasets Implement automated 3D modeling and generative AI workflows Explore practical applications in areas like computer vision/graphics, geospatial intelligence, scientific computing, robotics, and autonomous driving Build accurate digital environments that spatial AI solutions can leverage Florent Poux is an esteemed authority in the field of 3D data science who teaches and conducts research for top European universities. He's also head professor at the 3D Geodata Academy and innovation director for French Tech 120 companies.
The Generative Ai Practitioner S Guide
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Author : Arup Das
language : en
Publisher: TinyTechMedia LLC
Release Date : 2024-07-20
The Generative Ai Practitioner S Guide written by Arup Das and has been published by TinyTechMedia LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-20 with Computers categories.
Generative AI is revolutionizing the way organizations leverage technology to gain a competitive edge. However, as more companies experiment with and adopt AI systems, it becomes challenging for data and analytics professionals, AI practitioners, executives, technologists, and business leaders to look beyond the buzz and focus on the essential questions: Where should we begin? How do we initiate the process? What potential pitfalls should we be aware of? This TinyTechGuide offers valuable insights and practical recommendations on constructing a business case, calculating ROI, exploring real-life applications, and considering ethical implications. Crucially, it introduces five LLM patterns—author, retriever, extractor, agent, and experimental—to effectively implement GenAI systems within an organization. The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications bridges critical knowledge gaps for business leaders and practitioners, equipping them with a comprehensive toolkit to define a business case and successfully deploy GenAI. In today’s rapidly evolving world, staying ahead of the competition requires a deep understanding of these five implementation patterns and the potential benefits and risks associated with GenAI. Designed for business leaders, tech experts, and IT teams, this book provides real-life examples and actionable insights into GenAI’s transformative impact on various industries. Empower your organization with a competitive edge in today’s marketplace using The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications. Remember, it’s not the tech that’s tiny, just the book!™
Bio Inspired Computing
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Author : Dalia Kriksciuniene
language : en
Publisher: Springer Nature
Release Date : 2025-06-20
Bio Inspired Computing written by Dalia Kriksciuniene and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-20 with Computers categories.
This book presents 53 selected papers focused on Smart Health Care from the 14th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2023) and 13th World Congress on Information and Communication Technologies (WICT 2023), which was held in five different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India and in online mode. The 23rd International Conference on Hybrid Intelligent Systems (IBICA-WICT 2023) was focusing on synergistic combinations of multiple approaches to develop the next generation of bio-inspired computing and ICT systems. IBICA-WICT 2023 had contributions by authors from 36 countries. This book offers a valuable reference guide for all medical doctors, scientists, academicians, researchers, students, and practitioners in the field of artificial intelligence and smart health care.
Artificial Intelligence In Performance Driven Design
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Author : Narjes Abbasabadi
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-17
Artificial Intelligence In Performance Driven Design written by Narjes Abbasabadi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-17 with Architecture categories.
ARTIFICIAL INTELLIGENCE IN PERFORMANCE-DRIVEN DESIGN A definitive, interdisciplinary reference to using artificial intelligence technology and data-driven methodologies for sustainable design Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools explores the application of artificial intelligence (AI), specifically machine learning (ML), for performance modeling within the built environment. This work develops the theoretical foundations and methodological frameworks for utilizing AI/ML, with an emphasis on multi-scale modeling encompassing energy flows, environmental quality, and human systems. The book examines relevant practices, case studies, and computational tools that harness AI’s capabilities in modeling frameworks, enhancing the efficiency, accuracy, and integration of physics-based simulation, optimization, and automation processes. Furthermore, it highlights the integration of intelligent systems and digital twins throughout the lifecycle of the built environment, to enhance our understanding and management of these complex environments. This book also: Incorporates emerging technologies into practical ideas to improve performance analysis and sustainable design Presents data-driven methodologies and technologies that integrate into modeling and design platforms Shares valuable insights and tools for developing decarbonization pathways in urban buildings Includes contributions from expert researchers and educators across a range of related fields Artificial Intelligence in Performance-Driven Design is ideal for architects, engineers, planners, and researchers involved in sustainable design and the built environment. It’s also of interest to students of architecture, building science and technology, urban design and planning, environmental engineering, and computer science and engineering.
Deep Learning With Tensorflow And Keras
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Author : Amita Kapoor
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-10-06
Deep Learning With Tensorflow And Keras written by Amita Kapoor and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-06 with Computers categories.
Build cutting edge machine and deep learning systems for the lab, production, and mobile devices Key FeaturesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesImplement graph neural networks, transformers using Hugging Face and TensorFlow Hub, and joint and contrastive learningLearn cutting-edge machine and deep learning techniquesBook Description Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML. What you will learnLearn how to use the popular GNNs with TensorFlow to carry out graph mining tasksDiscover the world of transformers, from pretraining to fine-tuning to evaluating themApply self-supervised learning to natural language processing, computer vision, and audio signal processingCombine probabilistic and deep learning models using TensorFlow ProbabilityTrain your models on the cloud and put TF to work in real environmentsBuild machine learning and deep learning systems with TensorFlow 2.x and the Keras APIWho this book is for This hands-on machine learning book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow, and AutoML to build machine learning systems. Some machine learning knowledge would be useful. We don't assume TF knowledge.
Embedded Machine Learning For Cyber Physical Iot And Edge Computing
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Author : Sudeep Pasricha
language : en
Publisher: Springer Nature
Release Date : 2023-09-30
Embedded Machine Learning For Cyber Physical Iot And Edge Computing written by Sudeep Pasricha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-30 with Technology & Engineering categories.
This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits.
Multiscale Multimodal Medical Imaging
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Author : Xiang Li
language : en
Publisher: Springer Nature
Release Date : 2022-10-13
Multiscale Multimodal Medical Imaging written by Xiang Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-13 with Computers categories.
This book constitutes the refereed proceedings of the Third International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2022, held in conjunction with MICCAI 2022 in singapore, in September 2022. The 12 papers presented were carefully reviewed and selected from 18 submissions. The MMMI workshop aims to advance the state of the art in multi-scale multi-modal medical imaging, including algorithm development, implementation of methodology, and experimental studies. The papers focus on medical image analysis and machine learning, especially on machine learning methods for data fusion and multi-score learning.