Deep Natural Language Processing And Ai Applications For Industry 50

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Deep Natural Language Processing and AI Applications for Industry 5.0

Author : Tanwar, Poonam
Publisher : IGI Global
ISBN 13 : 1799877302
Total Pages : 240 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Natural Language Processing and AI Applications for Industry 5.0 by : Tanwar, Poonam

Download or read book Deep Natural Language Processing and AI Applications for Industry 5.0 written by Tanwar, Poonam and published by IGI Global. This book was released on 2021-06-25 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.

Deep Learning in Natural Language Processing

Author : Li Deng
Publisher : Springer
ISBN 13 : 9811052093
Total Pages : 329 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Deep Learning in Natural Language Processing by : Li Deng

Download or read book Deep Learning in Natural Language Processing written by Li Deng and published by Springer. This book was released on 2018-05-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.

Practical Natural Language Processing

Author : Sowmya Vajjala
Publisher : O'Reilly Media
ISBN 13 : 149205402X
Total Pages : 455 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Practical Natural Language Processing by : Sowmya Vajjala

Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective

Advanced Applications of Generative AI and Natural Language Processing Models

Author : Ahmed Jabbar Obaid
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Advanced Applications of Generative AI and Natural Language Processing Models by : Ahmed Jabbar Obaid

Download or read book Advanced Applications of Generative AI and Natural Language Processing Models written by Ahmed Jabbar Obaid and published by . This book was released on 2023-12-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Models equips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.

Applied Natural Language Processing in the Enterprise

Author : Ankur A. Patel
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492062545
Total Pages : 336 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Applied Natural Language Processing in the Enterprise by : Ankur A. Patel

Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Deep Learning for Natural Language Processing

Author : Karthiek Reddy Bokka
Publisher : Packt Publishing Ltd
ISBN 13 : 1838553673
Total Pages : 372 pages
Book Rating : 4.8/5 (385 download)

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Book Synopsis Deep Learning for Natural Language Processing by : Karthiek Reddy Bokka

Download or read book Deep Learning for Natural Language Processing written by Karthiek Reddy Bokka and published by Packt Publishing Ltd. This book was released on 2019-06-11 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key FeaturesGain insights into the basic building blocks of natural language processingLearn how to select the best deep neural network to solve your NLP problemsExplore convolutional and recurrent neural networks and long short-term memory networksBook Description Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts off by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In the later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search. By the end of this book, you will not only have sound knowledge of natural language processing but also be able to select the best text pre-processing and neural network models to solve a number of NLP issues. What you will learnUnderstand various pre-processing techniques for deep learning problemsBuild a vector representation of text using word2vec and GloVeCreate a named entity recognizer and parts-of-speech tagger with Apache OpenNLPBuild a machine translation model in KerasDevelop a text generation application using LSTMBuild a trigger word detection application using an attention modelWho this book is for If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.

Deep Neural Network Applications

Author : Hasmik Osipyan
Publisher : CRC Press
ISBN 13 : 0429556209
Total Pages : 158 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Deep Neural Network Applications by : Hasmik Osipyan

Download or read book Deep Neural Network Applications written by Hasmik Osipyan and published by CRC Press. This book was released on 2022-04-28 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is on the verge of fully ushering in the fourth industrial revolution, of which artificial intelligence (AI) is the most important new general-purpose technology. Like the steam engine that led to the widespread commercial use of driving machineries in the industries during the first industrial revolution; the internal combustion engine that gave rise to cars, trucks, and airplanes; electricity that caused the second industrial revolution through the discovery of direct and alternating current; and the Internet, which led to the emergence of the information age, AI is a transformational technology. It will cause a paradigm shift in the way’s problems are solved in every aspect of our lives, and, from it, innovative technologies will emerge. AI is the theory and development of machines that can imitate human intelligence in tasks such as visual perception, speech recognition, decision-making, and human language translation. This book provides a complete overview on the deep learning applications and deep neural network architectures. It also gives an overview on most advanced future-looking fundamental research in deep learning application in artificial intelligence. Research overview includes reasoning approaches, problem solving, knowledge representation, planning, learning, natural language processing, perception, motion and manipulation, social intelligence and creativity. It will allow the reader to gain a deep and broad knowledge of the latest engineering technologies of AI and Deep Learning and is an excellent resource for academic research and industry applications.

Real-World Natural Language Processing

Author : Masato Hagiwara
Publisher : Simon and Schuster
ISBN 13 : 1638350396
Total Pages : 334 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Real-World Natural Language Processing by : Masato Hagiwara

Download or read book Real-World Natural Language Processing written by Masato Hagiwara and published by Simon and Schuster. This book was released on 2021-12-21 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. In Real-world Natural Language Processing you will learn how to: Design, develop, and deploy useful NLP applications Create named entity taggers Build machine translation systems Construct language generation systems and chatbots Use advanced NLP concepts such as attention and transfer learning Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you’ll explore the core tools and techniques required to build a huge range of powerful NLP apps, including chatbots, language detectors, and text classifiers. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Training computers to interpret and generate speech and text is a monumental challenge, and the payoff for reducing labor and improving human/computer interaction is huge! Th e field of Natural Language Processing (NLP) is advancing rapidly, with countless new tools and practices. This unique book offers an innovative collection of NLP techniques with applications in machine translation, voice assistants, text generation, and more. About the book Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you’ll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you’ll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process. What's inside Design, develop, and deploy useful NLP applications Create named entity taggers Build machine translation systems Construct language generation systems and chatbots About the reader For Python programmers. No prior machine learning knowledge assumed. About the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009. He has interned at Google and Microsoft Research, and worked at Duolingo as a Senior Machine Learning Engineer. He now runs his own research and consulting company. Table of Contents PART 1 BASICS 1 Introduction to natural language processing 2 Your first NLP application 3 Word and document embeddings 4 Sentence classification 5 Sequential labeling and language modeling PART 2 ADVANCED MODELS 6 Sequence-to-sequence models 7 Convolutional neural networks 8 Attention and Transformer 9 Transfer learning with pretrained language models PART 3 PUTTING INTO PRODUCTION 10 Best practices in developing NLP applications 11 Deploying and serving NLP applications

Artificial Intelligence in Practice

Author : Bernard Marr
Publisher : John Wiley & Sons
ISBN 13 : 1119548969
Total Pages : 352 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Artificial Intelligence in Practice by : Bernard Marr

Download or read book Artificial Intelligence in Practice written by Bernard Marr and published by John Wiley & Sons. This book was released on 2019-04-15 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.

Deep Learning Research Applications for Natural Language Processing

Author : Ashok Kumar, L.
Publisher : IGI Global
ISBN 13 : 1668460033
Total Pages : 313 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Deep Learning Research Applications for Natural Language Processing by : Ashok Kumar, L.

Download or read book Deep Learning Research Applications for Natural Language Processing written by Ashok Kumar, L. and published by IGI Global. This book was released on 2022-12-09 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Humans have the most advanced method of communication, which is known as natural language. While humans can use computers to send voice and text messages to each other, computers do not innately know how to process natural language. In recent years, deep learning has primarily transformed the perspectives of a variety of fields in artificial intelligence (AI), including speech, vision, and natural language processing (NLP). The extensive success of deep learning in a wide variety of applications has served as a benchmark for the many downstream tasks in AI. The field of computer vision has taken great leaps in recent years and surpassed humans in tasks related to detecting and labeling objects thanks to advances in deep learning and neural networks. Deep Learning Research Applications for Natural Language Processing explains the concepts and state-of-the-art research in the fields of NLP, speech, and computer vision. It provides insights into using the tools and libraries in Python for real-world applications. Covering topics such as deep learning algorithms, neural networks, and advanced prediction, this premier reference source is an excellent resource for computational linguists, software engineers, IT managers, computer scientists, students and faculty of higher education, libraries, researchers, and academicians.

Natural Language Processing with PyTorch

Author : Delip Rao
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 149197818X
Total Pages : 256 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Natural Language Processing with PyTorch by : Delip Rao

Download or read book Natural Language Processing with PyTorch written by Delip Rao and published by "O'Reilly Media, Inc.". This book was released on 2019-01-22 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

Natural Language Processing Projects

Author : Akshay Kulkarni
Publisher : Apress
ISBN 13 : 9781484273852
Total Pages : 317 pages
Book Rating : 4.2/5 (738 download)

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Book Synopsis Natural Language Processing Projects by : Akshay Kulkarni

Download or read book Natural Language Processing Projects written by Akshay Kulkarni and published by Apress. This book was released on 2021-12-04 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libraries and algorithms to build end-to-end NLP projects. The book starts with an overview of natural language processing (NLP) and artificial intelligence to provide a quick refresher on algorithms. Next, it covers end-to-end NLP projects beginning with traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. From there, it delves into e-commerce related projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. Moving forward, it explains how to build systems to find similar sentences using contextual embedding, summarizing huge documents using recurrent neural networks (RNN), automatic word suggestion using long short-term memory networks (LSTM), and how to build a chatbot using transfer learning. It concludes with an exploration of next-generation AI and algorithms in the research space. By the end of this book, you will have the knowledge needed to solve various business problems using NLP techniques. What You Will Learn Implement full-fledged intelligent NLP applications with Python Translate real-world business problem on text data with NLP techniques Leverage machine learning and deep learning techniques to perform smart language processing Gain hands-on experience implementing end-to-end search engine information retrieval, text summarization, chatbots, text generation, document clustering and product classification, and more Who This Book Is For Data scientists, machine learning engineers, and deep learning professionals looking to build natural language applications using Python

Deep Learning Approaches for Spoken and Natural Language Processing

Author : Virender Kadyan
Publisher : Springer Nature
ISBN 13 : 3030797783
Total Pages : 171 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Deep Learning Approaches for Spoken and Natural Language Processing by : Virender Kadyan

Download or read book Deep Learning Approaches for Spoken and Natural Language Processing written by Virender Kadyan and published by Springer Nature. This book was released on 2022-01-01 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides insights into how deep learning techniques impact language and speech processing applications. The authors discuss the promise, limits and the new challenges in deep learning. The book covers the major differences between the various applications of deep learning and the classical machine learning techniques. The main objective of the book is to present a comprehensive survey of the major applications and research oriented articles based on deep learning techniques that are focused on natural language and speech signal processing. The book is relevant to academicians, research scholars, industrial experts, scientists and post graduate students working in the field of speech signal and natural language processing and would like to add deep learning to enhance capabilities of their work. Discusses current research challenges and future perspective about how deep learning techniques can be applied to improve NLP and speech processing applications; Presents and escalates the research trends and future direction of language and speech processing; Includes theoretical research, experimental results, and applications of deep learning.

Machine Learning and Deep Learning in Natural Language Processing

Author : Anitha S. Pillai
Publisher : CRC Press
ISBN 13 : 1000960897
Total Pages : 234 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Machine Learning and Deep Learning in Natural Language Processing by : Anitha S. Pillai

Download or read book Machine Learning and Deep Learning in Natural Language Processing written by Anitha S. Pillai and published by CRC Press. This book was released on 2023-10-18 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then they utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the NLP field, in particular about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content – like emotions, but also satirical expressions – and applications in the healthcare field. NLP has the potential to be a disruptive technology in various healthcare fields, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson’s disease, or help psychotherapists. This book is intended for a wide audience. Beginners will find useful chapters providing a general introduction to NLP techniques, while experienced professionals will appreciate the chapters about advanced management of emotion, empathy, and non-literal content.

Artificial Intelligence in Healthcare

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

ChatGPT for Enterprise

Author : Jothi Periasamy
Publisher : Jothi Periasamy
ISBN 13 :
Total Pages : 225 pages
Book Rating : 4./5 ( download)

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Book Synopsis ChatGPT for Enterprise by : Jothi Periasamy

Download or read book ChatGPT for Enterprise written by Jothi Periasamy and published by Jothi Periasamy. This book was released on 2023-06-29 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: With ChatGPT for Enterprise, large language models (LLM) are integrated into business processes and Generative AI visions become reality. To develop the book, several retail, energy, and education industry case studies were analyzed and explained from concept to implementation. By reading this book, readers will gain a deeper understanding of how to design and build business applications powered by ChatGPT and GPT. To accelerate the implementation of LLM through GPT and ChatGPT modules, we are sharing our GitHub links, as well as steps and procedures for training, testing, tuning, and deploying modules on Google Cloud Platform (GCP). While this book empowers both business and technical users, it is primarily intended for those interested in using CGPT or ChatGPT models in Generative AI or LLM. For professionals and those just getting started with Generative AI and LLM, this book is an excellent starting point for understanding foundational concepts and implementing advanced use cases using Google Cloud Platform.

Natural Language Processing with AWS AI Services

Author : Mona M
Publisher : Packt Publishing Ltd
ISBN 13 : 1801815488
Total Pages : 508 pages
Book Rating : 4.8/5 (18 download)

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Book Synopsis Natural Language Processing with AWS AI Services by : Mona M

Download or read book Natural Language Processing with AWS AI Services written by Mona M and published by Packt Publishing Ltd. This book was released on 2021-11-26 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work through interesting real-life business use cases to uncover valuable insights from unstructured text using AWS AI services Key FeaturesGet to grips with AWS AI services for NLP and find out how to use them to gain strategic insightsRun Python code to use Amazon Textract and Amazon Comprehend to accelerate business outcomesUnderstand how you can integrate human-in-the-loop for custom NLP use cases with Amazon A2IBook Description Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production. To start with, you'll understand the importance of NLP in today's business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic. Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications. What you will learnAutomate various NLP workflows on AWS to accelerate business outcomesUse Amazon Textract for text, tables, and handwriting recognition from images and PDF filesGain insights from unstructured text in the form of sentiment analysis, topic modeling, and more using Amazon ComprehendSet up end-to-end document processing pipelines to understand the role of humans in the loopDevelop NLP-based intelligent search solutions with just a few lines of codeCreate both real-time and batch document processing pipelines using PythonWho this book is for If you're an NLP developer or data scientist looking to get started with AWS AI services to implement various NLP scenarios quickly, this book is for you. It will show you how easy it is to integrate AI in applications with just a few lines of code. A basic understanding of machine learning (ML) concepts is necessary to understand the concepts covered. Experience with Jupyter notebooks and Python will be helpful.