The Art and Science of Transformer: A Breakthrough in Modern AI and NLP PDF Download
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Author: Debstuti Das
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 94
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Book Description
The Art and Science of Transformer: A Breakthrough in the Modern Artificial Intelligence and Natural Language Processing Are you ready to dive deep into the world of AI and unlock the secrets of one of the most revolutionary advancements in natural language processing? “The Art and Science of Transformer" is your definitive guide to understanding the powerful transformer model that has transformed the landscape of artificial intelligence. This book is designed for anyone eager to understand the revolutionary transformer architecture that has significantly advanced the field of artificial intelligence. Whether you are a student, an aspiring data scientist, or a professional looking to expand your knowledge, this book aims to make the complex world of transformers accessible and understandable. (This is a Kindle Print Replica Book, so can be opened in mobile, tab or any other device using Kindle App only, Not compatible with Kindle device yet) About the Boo In "The Art and Science of Transformer," you'll embark on a comprehensive journey that begins with the foundational concepts of word embedding and progresses through the intricate workings of attention mechanisms, self-attention, positional encoding, and multithreaded attention, culminating in a thorough exploration of the entire transformer architecture. What You Will Learn: Word Embedding: Grasp the basics of representing words in vector space, setting the stage for deeper understanding. Attention Mechanism: Discover how attention mechanisms enable models to focus on relevant parts of input data, enhancing performance. Self-Attention: Learn about self-attention and its pivotal role in allowing models to weigh the importance of different words within a sequence. Positional Encoding: Understand how positional encoding helps transformers retain the order of words, a crucial aspect of sequence processing. Multi-Headed Attention: Dive into the concept of multi-headed attention and its contribution. Transformer Architecture: Explore the complete transformer architecture, from encoder and decoder stacks to the whole architecture. Why This Book? Comprehensive Coverage: It provides a thorough overview of transformer architecture, covering key concepts. Clear Explanations: The book offers clear and concise explanations of complex topics, making it accessible to readers at various levels of expertise. Insightful Insights: The book provides insightful insights into the design principles behind transformer architecture, helping readers develop a deeper appreciation for its inner workings. Overall, this book is an invaluable resource for anyone interested in transformer architecture, from beginners looking to get started to experienced practitioners seeking to enhance their understanding. Who Should Read This Book? AI Enthusiasts: Anyone interested in the latest advancements in artificial intelligence and natural language processing. Data Scientists and Engineers: Professionals looking to enhance their understanding of transformer models in their projects. Students and Academics: Learners seeking a thorough and practical guide to one of the most impactful AI architectures today.
Author: Debstuti Das
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 94
Get Book Here
Book Description
The Art and Science of Transformer: A Breakthrough in the Modern Artificial Intelligence and Natural Language Processing Are you ready to dive deep into the world of AI and unlock the secrets of one of the most revolutionary advancements in natural language processing? “The Art and Science of Transformer" is your definitive guide to understanding the powerful transformer model that has transformed the landscape of artificial intelligence. This book is designed for anyone eager to understand the revolutionary transformer architecture that has significantly advanced the field of artificial intelligence. Whether you are a student, an aspiring data scientist, or a professional looking to expand your knowledge, this book aims to make the complex world of transformers accessible and understandable. (This is a Kindle Print Replica Book, so can be opened in mobile, tab or any other device using Kindle App only, Not compatible with Kindle device yet) About the Boo In "The Art and Science of Transformer," you'll embark on a comprehensive journey that begins with the foundational concepts of word embedding and progresses through the intricate workings of attention mechanisms, self-attention, positional encoding, and multithreaded attention, culminating in a thorough exploration of the entire transformer architecture. What You Will Learn: Word Embedding: Grasp the basics of representing words in vector space, setting the stage for deeper understanding. Attention Mechanism: Discover how attention mechanisms enable models to focus on relevant parts of input data, enhancing performance. Self-Attention: Learn about self-attention and its pivotal role in allowing models to weigh the importance of different words within a sequence. Positional Encoding: Understand how positional encoding helps transformers retain the order of words, a crucial aspect of sequence processing. Multi-Headed Attention: Dive into the concept of multi-headed attention and its contribution. Transformer Architecture: Explore the complete transformer architecture, from encoder and decoder stacks to the whole architecture. Why This Book? Comprehensive Coverage: It provides a thorough overview of transformer architecture, covering key concepts. Clear Explanations: The book offers clear and concise explanations of complex topics, making it accessible to readers at various levels of expertise. Insightful Insights: The book provides insightful insights into the design principles behind transformer architecture, helping readers develop a deeper appreciation for its inner workings. Overall, this book is an invaluable resource for anyone interested in transformer architecture, from beginners looking to get started to experienced practitioners seeking to enhance their understanding. Who Should Read This Book? AI Enthusiasts: Anyone interested in the latest advancements in artificial intelligence and natural language processing. Data Scientists and Engineers: Professionals looking to enhance their understanding of transformer models in their projects. Students and Academics: Learners seeking a thorough and practical guide to one of the most impactful AI architectures today.
Author: Debstuti Das
Publisher: Notion Press
ISBN:
Category : Education
Languages : en
Pages : 0
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Book Description
The Art and Science of Transformer: A Breakthrough in the Modern AI and NLP Are you ready to dive deep into the world of AI and unlock the secrets of one of the most revolutionary advancements in natural language processing? This book is your definitive guide. Whether you are a student, an aspiring data scientist, or a professional looking to expand your knowledge, this book aims to make the complex world of transformers accessible and understandable with its comprehensive coverage, clear explanations, and insightful guidance. What You Will Learn: Token Embedding: Grasp the basics of representing words or tokens in vector space, setting the stage for deeper understanding. Attention Mechanism: Discover how attention mechanisms enable models to focus on relevant parts of input data, enhancing performance. Self-Attention: Learn about self-attention and its pivotal role in allowing models to weigh the importance of different words within a sequence. Positional Encoding: Understand how positional encoding helps transformers retain the order of words, a crucial aspect of sequence processing. Multi-Headed Attention: Dive into the concept of multi-headed attention and its contribution. Transformer Architecture: Explore the complete transformer architecture, from encoder and decoder stacks to the whole architecture. GPT and BERT Architecture: Explore how these models utilize Transformer architecture to perform tasks like text generation, sentiment analysis, and more.
Author: Reeshabh Choudhary
Publisher: Reeshabh Choudhary
ISBN: 9360390674
Category : Computers
Languages : en
Pages : 385
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Book Description
This book is about uncovering a journey of how Software programming evolved and AI based technologies came into foray. This book tries to connect the dots for a new programmer, starting on his/her journey into the software development world. With so many technologies evolving around every single day, with new breaches in innovation in the field of AI/ML or Data Science, which gets the job done in a whisker, as programmers we tend to think, where do we stand? The journey or even the thought of making sense of everything around us can be quite overwhelming. From the days of C/C++ programming to Java/C#/JavaScript and Python/MATLAB/R, programming has exponentially evolved. And so, does the computational ability of computers, which also helped in faster execution of these programs, but also to extraction of Information from the data generated via the applications developed by these programs. In this digital age, everything seems to be connected and yet we sweat making sense of all these connections. In the interconnected digital age, understanding the connections between various technologies can be challenging. The book aims to bridge some of these gaps by providing readers with a foundational understanding of how programming, data, and machine learning are interconnected. By grasping these fundamentals, software developers can connect the dots according to their specific requirements.
Author: Ronald M. Razmi
Publisher: John Wiley & Sons
ISBN: 1394240171
Category : Computers
Languages : en
Pages : 373
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Book Description
Explores the transformative impact of artificial intelligence (AI) on the healthcare industry AI Doctor: The Rise of Artificial Intelligence in Healthcare provides a timely and authoritative overview of the current impact and future potential of AI technology in healthcare. With a reader-friendly narrative style, this comprehensive guide traces the evolution of AI in healthcare, describes methodological breakthroughs, drivers and barriers of its adoption, discusses use cases across clinical medicine, administration and operations, and life sciences, and examines the business models for the entrepreneurs, investors, and customers. Detailed yet accessible chapters help those in the business and practice of healthcare recognize the remarkable potential of AI in areas such as drug discovery and development, diagnostics, therapeutics, clinical workflows, personalized medicine, early disease prediction, population health management, and healthcare administration and operations. Throughout the text, author Ronald M. Razmi, MD offers valuable insights on harnessing AI to improve health of the world population, develop more efficient business models, accelerate long-term economic growth, and optimize healthcare budgets. Addressing the potential impact of AI on the clinical practice of medicine, the business of healthcare, and opportunities for investors, AI Doctor: The Rise of Artificial Intelligence in Healthcare: Discusses what AI is currently doing in healthcare and its direction in the next decade Examines the development and challenges for medical algorithms Identifies the applications of AI in diagnostics, therapeutics, population health, clinical workflows, administration and operations, discovery and development of new clinical paradigms and more Presents timely and relevant information on rapidly expanding generative AI technologies, such as Chat GPT Describes the analysis that needs to be made by entrepreneurs and investors as they evaluate building or investing in health AI solutions Features a wealth of relatable real-world examples that bring technical concepts to life Explains the role of AI in the development of vaccines, diagnostics, and therapeutics during the COVID-19 pandemic AI Doctor: The Rise of Artificial Intelligence in Healthcare. A Guide for Users, Buyers, Builders, and Investors is a must-read for healthcare professionals, researchers, investors, entrepreneurs, medical and nursing students, and those building or designing systems for the commercial marketplace. The book's non-technical and reader-friendly narrative style also makes it an ideal read for everyone interested in learning about how AI will improve health and healthcare in the coming decades.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309684234
Category : Computers
Languages : en
Pages : 148
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Book Description
Information technology (IT) is widely understood to be the enabling technology of the 21st century. IT has transformed, and continues to transform, all aspects of our lives: commerce and finance, education, energy, health care, manufacturing, government, national security, transportation, communications, entertainment, science, and engineering. IT and its impact on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow in size and importance. IT’s impacts on the U.S. economyâ€"both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€"continue to grow. IT enabled innovation and advances in IT products and services draw on a deep tradition of research and rely on sustained investment and a uniquely strong partnership in the United States among government, industry, and universities. Past returns on federal investments in IT research have been extraordinary for both U.S. society and the U.S. economy. This IT innovation ecosystem fuels a virtuous cycle of innovation with growing economic impact. Building on previous National Academies work, this report describes key features of the IT research ecosystem that fuel IT innovation and foster widespread and longstanding impact across the U.S. economy. In addition to presenting established computing research areas and industry sectors, it also considers emerging candidates in both categories.
Author: Steven Bird
Publisher: "O'Reilly Media, Inc."
ISBN: 0596555717
Category : Computers
Languages : en
Pages : 506
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Book Description
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Author: Kai-Fu Lee
Publisher: Crown Currency
ISBN: 0593238311
Category : Social Science
Languages : en
Pages : 497
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Book Description
How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.
Author: Jon Krohn
Publisher: Addison-Wesley Professional
ISBN: 0135121728
Category : Computers
Languages : en
Pages : 725
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Book Description
"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Author: Ankur A. Patel
Publisher: "O'Reilly Media, Inc."
ISBN: 1492062545
Category : Computers
Languages : en
Pages : 336
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Book Description
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
Author: Rajshree Srivastava
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110676125
Category : Computers
Languages : en
Pages : 182
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Book Description
Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.
