Author: Arindam Dey
Publisher: John Wiley & Sons
ISBN: 1394214111
Category : Computers
Languages : en
Pages : 485
Book Description
Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques. Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline. How Machine Learning is Innovating Today's World is a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries. It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include: An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processing explores the evaluation of English language readability using ML models a detailed study of text analysis for information retrieval through natural language processing the application of reinforcement learning approaches to supply chain management the performance analysis of converting algorithms to source code using natural language processing in Java presents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniques a comparative study of different techniques of text-to-SQL query conversion the classification of livestock diseases using ML algorithms ML in image enhancement techniques the efficient leader selection for inter-cluster flying ad-hoc networks a comprehensive survey of applications powered by GPT-3 and DALL-E recommender systems' domain of application reviews mood detection, emoji generation, and classification using tokenization and CNN variations of the exam scheduling problem using graph coloring the intersection of software engineering and machine learning applications explores ML strategies for indeterminate information systems in complex bipolar neutrosophic environments ML applications in healthcare, in battery management systems, and the rise of AI-generated news videos how to enhance resource management in precision farming through AI-based irrigation optimization. Audience The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.
How Machine Learning is Innovating Today's World
Author: Arindam Dey
Publisher: John Wiley & Sons
ISBN: 1394214111
Category : Computers
Languages : en
Pages : 485
Book Description
Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques. Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline. How Machine Learning is Innovating Today's World is a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries. It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include: An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processing explores the evaluation of English language readability using ML models a detailed study of text analysis for information retrieval through natural language processing the application of reinforcement learning approaches to supply chain management the performance analysis of converting algorithms to source code using natural language processing in Java presents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniques a comparative study of different techniques of text-to-SQL query conversion the classification of livestock diseases using ML algorithms ML in image enhancement techniques the efficient leader selection for inter-cluster flying ad-hoc networks a comprehensive survey of applications powered by GPT-3 and DALL-E recommender systems' domain of application reviews mood detection, emoji generation, and classification using tokenization and CNN variations of the exam scheduling problem using graph coloring the intersection of software engineering and machine learning applications explores ML strategies for indeterminate information systems in complex bipolar neutrosophic environments ML applications in healthcare, in battery management systems, and the rise of AI-generated news videos how to enhance resource management in precision farming through AI-based irrigation optimization. Audience The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.
Publisher: John Wiley & Sons
ISBN: 1394214111
Category : Computers
Languages : en
Pages : 485
Book Description
Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques. Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline. How Machine Learning is Innovating Today's World is a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries. It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include: An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processing explores the evaluation of English language readability using ML models a detailed study of text analysis for information retrieval through natural language processing the application of reinforcement learning approaches to supply chain management the performance analysis of converting algorithms to source code using natural language processing in Java presents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniques a comparative study of different techniques of text-to-SQL query conversion the classification of livestock diseases using ML algorithms ML in image enhancement techniques the efficient leader selection for inter-cluster flying ad-hoc networks a comprehensive survey of applications powered by GPT-3 and DALL-E recommender systems' domain of application reviews mood detection, emoji generation, and classification using tokenization and CNN variations of the exam scheduling problem using graph coloring the intersection of software engineering and machine learning applications explores ML strategies for indeterminate information systems in complex bipolar neutrosophic environments ML applications in healthcare, in battery management systems, and the rise of AI-generated news videos how to enhance resource management in precision farming through AI-based irrigation optimization. Audience The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.
How Machine Learning is Innovating Today's World
Author: Arindam Dey
Publisher: John Wiley & Sons
ISBN: 1394214138
Category : Computers
Languages : en
Pages : 489
Book Description
Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques. Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline. How Machine Learning is Innovating Today's World is a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries. It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include: An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processing explores the evaluation of English language readability using ML models a detailed study of text analysis for information retrieval through natural language processing the application of reinforcement learning approaches to supply chain management the performance analysis of converting algorithms to source code using natural language processing in Java presents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniques a comparative study of different techniques of text-to-SQL query conversion the classification of livestock diseases using ML algorithms ML in image enhancement techniques the efficient leader selection for inter-cluster flying ad-hoc networks a comprehensive survey of applications powered by GPT-3 and DALL-E recommender systems' domain of application reviews mood detection, emoji generation, and classification using tokenization and CNN variations of the exam scheduling problem using graph coloring the intersection of software engineering and machine learning applications explores ML strategies for indeterminate information systems in complex bipolar neutrosophic environments ML applications in healthcare, in battery management systems, and the rise of AI-generated news videos how to enhance resource management in precision farming through AI-based irrigation optimization. Audience The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.
Publisher: John Wiley & Sons
ISBN: 1394214138
Category : Computers
Languages : en
Pages : 489
Book Description
Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques. Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline. How Machine Learning is Innovating Today's World is a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries. It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include: An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processing explores the evaluation of English language readability using ML models a detailed study of text analysis for information retrieval through natural language processing the application of reinforcement learning approaches to supply chain management the performance analysis of converting algorithms to source code using natural language processing in Java presents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniques a comparative study of different techniques of text-to-SQL query conversion the classification of livestock diseases using ML algorithms ML in image enhancement techniques the efficient leader selection for inter-cluster flying ad-hoc networks a comprehensive survey of applications powered by GPT-3 and DALL-E recommender systems' domain of application reviews mood detection, emoji generation, and classification using tokenization and CNN variations of the exam scheduling problem using graph coloring the intersection of software engineering and machine learning applications explores ML strategies for indeterminate information systems in complex bipolar neutrosophic environments ML applications in healthcare, in battery management systems, and the rise of AI-generated news videos how to enhance resource management in precision farming through AI-based irrigation optimization. Audience The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.
Deploying Machine Learning
Author: Robbie Allen
Publisher: Addison-Wesley Professional
ISBN: 9780135226209
Category : Computers
Languages : en
Pages : 99998
Book Description
Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
Publisher: Addison-Wesley Professional
ISBN: 9780135226209
Category : Computers
Languages : en
Pages : 99998
Book Description
Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
The Economics of Artificial Intelligence
Author: Ajay Agrawal
Publisher: University of Chicago Press
ISBN: 0226833127
Category : Business & Economics
Languages : en
Pages : 172
Book Description
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Publisher: University of Chicago Press
ISBN: 0226833127
Category : Business & Economics
Languages : en
Pages : 172
Book Description
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
Artificial Intelligence
Author: Harvard Business Review
Publisher: HBR Insights
ISBN: 9781633697898
Category : Business & Economics
Languages : en
Pages : 160
Book Description
Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.
Publisher: HBR Insights
ISBN: 9781633697898
Category : Business & Economics
Languages : en
Pages : 160
Book Description
Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.
Human-Centered AI
Author: Ben Shneiderman
Publisher: Oxford University Press
ISBN: 0192845292
Category : Computers
Languages : en
Pages : 390
Book Description
The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.
Publisher: Oxford University Press
ISBN: 0192845292
Category : Computers
Languages : en
Pages : 390
Book Description
The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.
AI for Marketing and Product Innovation
Author: A. K. Pradeep
Publisher: John Wiley & Sons
ISBN: 111948409X
Category : Business & Economics
Languages : en
Pages : 214
Book Description
Get on board the next massive marketing revolution AI for Marketing and Product Innovation offers creatives and marketing professionals a non-tech guide to artificial intelligence (AI) and machine learning (ML)—twin technologies that stand poised to revolutionize the way we sell. The future is here, and we are in the thick of it; AI and ML are already in our lives every day, whether we know it or not. The technology continues to evolve and grow, but the capabilities that make these tools world-changing for marketers are already here—whether we use them or not. This book helps you lean into the curve and take advantage of AI’s unparalleled and rapidly expanding power. More than a simple primer on the technology, this book goes beyond the “what” to show you the “how”: How do we use AI and ML in ways that speak to the human spirit? How to we translate cold technological innovation into creative tools that forge deep human connections? Written by a team of experts at the intersection of neuroscience, technology, and marketing, this book shows you the ins and outs of these groundbreaking technological tools. Understand AI and ML technology in layman’s terms Harness the twin technologies unparalleled power to transform marketing Learn which skills and resources you need to use AI and ML effectively Employ AI and ML in ways that resonate meaningfully with customers Learn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI Discover the true impact of AI and ML from real-world examples, and learn the thinking, best practices, and metrics you need to capture this lightning and take the next massive leap in the evolution of customer connection. AI for Marketing and Product Innovation shows you everything you need to know to get on board.
Publisher: John Wiley & Sons
ISBN: 111948409X
Category : Business & Economics
Languages : en
Pages : 214
Book Description
Get on board the next massive marketing revolution AI for Marketing and Product Innovation offers creatives and marketing professionals a non-tech guide to artificial intelligence (AI) and machine learning (ML)—twin technologies that stand poised to revolutionize the way we sell. The future is here, and we are in the thick of it; AI and ML are already in our lives every day, whether we know it or not. The technology continues to evolve and grow, but the capabilities that make these tools world-changing for marketers are already here—whether we use them or not. This book helps you lean into the curve and take advantage of AI’s unparalleled and rapidly expanding power. More than a simple primer on the technology, this book goes beyond the “what” to show you the “how”: How do we use AI and ML in ways that speak to the human spirit? How to we translate cold technological innovation into creative tools that forge deep human connections? Written by a team of experts at the intersection of neuroscience, technology, and marketing, this book shows you the ins and outs of these groundbreaking technological tools. Understand AI and ML technology in layman’s terms Harness the twin technologies unparalleled power to transform marketing Learn which skills and resources you need to use AI and ML effectively Employ AI and ML in ways that resonate meaningfully with customers Learn practical examples of how to reinvest product innovation, brand building, targeted marketing and media measurement to connect with people and enhance ROI Discover the true impact of AI and ML from real-world examples, and learn the thinking, best practices, and metrics you need to capture this lightning and take the next massive leap in the evolution of customer connection. AI for Marketing and Product Innovation shows you everything you need to know to get on board.
Artificial Intelligence in Society
Author: OECD
Publisher: OECD Publishing
ISBN: 9264545190
Category :
Languages : en
Pages : 152
Book Description
The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises.
Publisher: OECD Publishing
ISBN: 9264545190
Category :
Languages : en
Pages : 152
Book Description
The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises.
Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Book Description
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
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Book Description
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
Encyclopedia of Data Science and Machine Learning
Author: Wang, John
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296
Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296
Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.