Design of Intelligent Applications using Machine Learning and Deep Learning Techniques

Design of Intelligent Applications using Machine Learning and Deep Learning Techniques

Author: Ramchandra Sharad Mangrulkar

Publisher: CRC Press

Published: 2021-08-15

Total Pages: 446

ISBN-13: 1000423832

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Machine learning (ML) and deep learning (DL) algorithms are invaluable resources for Industry 4.0 and allied areas and are considered as the future of computing. A subfield called neural networks, to recognize and understand patterns in data, helps a machine carry out tasks in a manner similar to humans. The intelligent models developed using ML and DL are effectively designed and are fully investigated – bringing in practical applications in many fields such as health care, agriculture and security. These algorithms can only be successfully applied in the context of data computing and analysis. Today, ML and DL have created conditions for potential developments in detection and prediction. Apart from these domains, ML and DL are found useful in analysing the social behaviour of humans. With the advancements in the amount and type of data available for use, it became necessary to build a means to process the data and that is where deep neural networks prove their importance. These networks are capable of handling a large amount of data in such fields as finance and images. This book also exploits key applications in Industry 4.0 including: · Fundamental models, issues and challenges in ML and DL. · Comprehensive analyses and probabilistic approaches for ML and DL. · Various applications in healthcare predictions such as mental health, cancer, thyroid disease, lifestyle disease and cardiac arrhythmia. · Industry 4.0 applications such as facial recognition, feather classification, water stress prediction, deforestation control, tourism and social networking. · Security aspects of Industry 4.0 applications suggest remedial actions against possible attacks and prediction of associated risks. - Information is presented in an accessible way for students, researchers and scientists, business innovators and entrepreneurs, sustainable assessment and management professionals. This book equips readers with a knowledge of data analytics, ML and DL techniques for applications defined under the umbrella of Industry 4.0. This book offers comprehensive coverage, promising ideas and outstanding research contributions, supporting further development of ML and DL approaches by applying intelligence in various applications.


Deep Learning Applications and Intelligent Decision Making in Engineering

Deep Learning Applications and Intelligent Decision Making in Engineering

Author: Senthilnathan, Karthikrajan

Publisher: IGI Global

Published: 2020-10-23

Total Pages: 332

ISBN-13: 1799821102

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Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.


Deep Learning Applications, Volume 2

Deep Learning Applications, Volume 2

Author: M. Arif Wani

Publisher: Springer

Published: 2020-12-14

Total Pages: 300

ISBN-13: 9789811567582

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This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.


Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering

Author: Jingzheng Ren

Publisher: Elsevier

Published: 2021-06-05

Total Pages: 542

ISBN-13: 012821743X

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Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering


Fundamentals of Deep Learning

Fundamentals of Deep Learning

Author: Nikhil Buduma

Publisher: "O'Reilly Media, Inc."

Published: 2017-05-25

Total Pages: 272

ISBN-13: 1491925566

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With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning


Machine Learning and IoT for Intelligent Systems and Smart Applications

Machine Learning and IoT for Intelligent Systems and Smart Applications

Author: Madhumathy P

Publisher: CRC Press

Published: 2021-11-17

Total Pages: 243

ISBN-13: 1000484963

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The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.


Data Science

Data Science

Author: Pallavi Vijay Chavan

Publisher: CRC Press

Published: 2022-08-15

Total Pages: 323

ISBN-13: 1000613429

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This book covers the topic of data science in a comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached its maturity. The book starts with the basic concepts of data science. It highlights the types of data and their use and importance, followed by a discussion on a wide range of applications of data science and widely used techniques in data science. Key Features • Provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science. • Presents predictive outcomes by applying data science techniques to real-life applications. • Provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. • Gives the reader a variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful.


Information Systems Design and Intelligent Applications

Information Systems Design and Intelligent Applications

Author: Vikrant Bhateja

Publisher: Springer

Published: 2018-03-01

Total Pages: 1112

ISBN-13: 9811075123

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The book is a collection of high-quality peer-reviewed research papers presented at International Conference on Information System Design and Intelligent Applications (INDIA 2017) held at Duy Tan University, Da Nang, Vietnam during 15-17 June 2017. The book covers a wide range of topics of computer science and information technology discipline ranging from image processing, database application, data mining, grid and cloud computing, bioinformatics and many others. The various intelligent tools like swarm intelligence, artificial intelligence, evolutionary algorithms, bio-inspired algorithms have been well applied in different domains for solving various challenging problems.


Information Systems Design and Intelligent Applications

Information Systems Design and Intelligent Applications

Author: Suresh Chandra Satapathy

Publisher: Springer

Published: 2019-01-04

Total Pages: 459

ISBN-13: 9811333386

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The book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Information System Design and Intelligent Applications (INDIA 2018), which was held at the Universite des Mascareignes, Mauritius from July 19 to 21, 2018. It covers a wide range of topics in computer science and information technology, from image processing, database applications and data mining, to grid and cloud computing, bioinformatics and many more. The intelligent tools discussed, e.g. swarm intelligence, artificial intelligence, evolutionary algorithms, and bio-inspired algorithms, are currently being applied to solve challenging problems in various domains.