Innovations in Machine and Deep Learning

Innovations in Machine and Deep Learning PDF Author: Gilberto Rivera
Publisher: Springer Nature
ISBN: 3031406885
Category : Computers
Languages : en
Pages : 506

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Book Description
In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts. The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0. This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.

Innovations in Machine and Deep Learning

Innovations in Machine and Deep Learning PDF Author: Gilberto Rivera
Publisher: Springer Nature
ISBN: 3031406885
Category : Computers
Languages : en
Pages : 506

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Book Description
In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts. The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0. This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.

Practical Machine Learning

Practical Machine Learning PDF Author: Ted Dunning
Publisher: "O'Reilly Media, Inc."
ISBN: 1491915722
Category : Machine learning
Languages : en
Pages : 55

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Book Description
Annotation Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for business production settingsand demonstrates how even a small-scale development team can design an effective large-scale recommendation system. Apache Mahout committers Ted Dunning and Ellen Friedman walk you through a design that relies on careful simplification. Youll learn how to collect the right data, analyze it with an algorithm from the Mahout library, and then easily deploy the recommender using search technology, such as Apache Solr or Elasticsearch. Powerful and effective, this efficient combination does learning offline and delivers rapid response recommendations in real time. Understand the tradeoffs between simple and complex recommendersCollect user data that tracks user actionsrather than their ratingsPredict what a user wants based on behavior by others, using Mahoutfor co-occurrence analysisUse search technology to offer recommendations in real time, complete with item metadataWatch the recommender in action with a music service exampleImprove your recommender with dithering, multimodal recommendation, and other techniques.

Machine Learning for Healthcare Applications

Machine Learning for Healthcare Applications PDF Author: Sachi Nandan Mohanty
Publisher: John Wiley & Sons
ISBN: 1119791812
Category : Computers
Languages : en
Pages : 418

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Book Description
When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Innovations in Intelligent Machines - 1

Innovations in Intelligent Machines - 1 PDF Author: Javaan Singh Chahl
Publisher: Springer
ISBN: 3540726969
Category : Technology & Engineering
Languages : en
Pages : 270

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Book Description
This book is a collection of chapters on the state of art in the area of intelligent machines. This research provides a sound basis to make autonomous systems human-like. The contributions include an introduction to intelligent machines; supervisory control of multiple UAVs; and intelligent autonomous UAV task allocation. Also included is material on UAV path planning; dynamic path planning ; state estimation of micro air vehicles and architecture for soccer playing robots, as well as robot perception.

Innovations and Applications of AI, IoT, and Cognitive Technologies

Innovations and Applications of AI, IoT, and Cognitive Technologies PDF Author: Jingyuan Zhao
Publisher:
ISBN: 9781799868712
Category :
Languages : en
Pages :

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Book Description


Innovations in Machine Learning

Innovations in Machine Learning PDF Author: Dawn E. Holmes
Publisher: Springer
ISBN: 3540334866
Category : Technology & Engineering
Languages : en
Pages : 276

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Book Description
Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.

Deploying Machine Learning

Deploying Machine Learning PDF Author: Robbie Allen
Publisher: Addison-Wesley Professional
ISBN: 9780135226209
Category : Computers
Languages : en
Pages : 99998

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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.

Advances in Financial Machine Learning

Advances in Financial Machine Learning PDF Author: Marcos Lopez de Prado
Publisher: John Wiley & Sons
ISBN: 1119482119
Category : Business & Economics
Languages : en
Pages : 400

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Book Description
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Innovations in Machine Learning and IoT for Water Management

Innovations in Machine Learning and IoT for Water Management PDF Author: Kumar, Abhishek
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 331

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Book Description
Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship. This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages.

Artificial Intelligence

Artificial Intelligence PDF Author: Rashmi Priyadarshini
Publisher: CRC Press
ISBN: 1000615081
Category : Computers
Languages : en
Pages : 301

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Book Description
Artificial Intelligence: Applications and Innovations is a book about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Key Features Provides insight into prospective research and application areas related to industry and technology Discusses industry- based inputs on success stories of technology adoption Discusses technology applications from a research perspective in the field of AI Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning This book is primarily aimed at graduates and post- graduates in computer science, information technology, civil engineering, electronics and electrical engineering and management.