Machine Learning and Deep Learning in Real-Time Applications by Mehul Mahrishi
Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.-
5G Internet of Things and Changing Standards for Computing and Electronic Systems
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Hydrogen Fuel Cell Technology for Stationary Applications
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Innovations in the Industrial Internet of Things (IIoT) and Smart Factory
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Handbook of Research on AI Methods and Applications in Computer Engineering
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Open Source Software for Statistical Analysis of Big Data
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IoT Architectures, Models, and Platforms for Smart City Applications
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Handbook of Research on 5G Networks and Advancements in Computing, Electronics, and Electrical Engineering
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Tools and Technologies for the Development of Cyber-Physical Systems
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Innovative Applications of Nanowires for Circuit Design
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Pattern Recognition Applications in Engineering
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Computational Methodologies for Electrical and Electronics Engineers
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Emerging Applications of Fuzzy Algebraic Structures
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Advanced Applications of Fractional Differential Operators to Science and Technology
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Optimizing and Measuring Smart Grid Operation and Control
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Machine Learning for Environmental Monitoring in Wireless Sensor Networks
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Edible Electronics for Smart Technology Solutions
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Developing Digital Inclusion Through Globalization and Digitalization
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Nature-Inspired Optimization Algorithms for Cyber-Physical Systems
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Emerging Trends in Cloud Computing Analytics, Scalability, and Service Models
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Driving Transformative Technology Trends With Cloud Computing
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Navigating the Augmented and Virtual Frontiers in Engineering
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Impact and Potential of Machine Learning in the Metaverse
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Harnessing Green and Circular Skills for Digital Transformation
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Battery-Free Sensor Networks for Sustainable Next-Generation IoT Connectivity
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Advancing Intelligent Networks Through Distributed Optimization
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Digital Technologies for Sustainability and Quality Control
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Navigating Cyber-Physical Systems With Cutting-Edge Technologies
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Modern SuperHyperSoft Computing Trends in Science and Technology
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Multifaceted Uses of Cutting-Edge Technologies and Social Concerns
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Handbook of Research on Engineering Innovations and Technology Management in Organizations
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Research Advancements in Smart Technology, Optimization, and Renewable Energy
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Principles and Theories of Data Mining With RapidMiner
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Industrial Internet of Things and Cyber-Physical Systems
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Energy Systems Design for Low-Power Computing
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Structural and Functional Aspects of Biocomputing Systems for Data Processing
| SKU | Unavailable |
| ISBN 13 | 9781799830955 |
| ISBN 10 | 1799830950 |
| Title | Machine Learning and Deep Learning in Real-Time Applications |
| Author | Mehul Mahrishi |
| Series | Advances In Computer And Electrical Engineering Ser |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | IGI Global |
| Year published | 2020-04-24 |
| Number of pages | 344 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |