Machine Learning For Industrial Applications

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Automated Machine Learning And Industrial Applications
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Author : E. Gangadevi
language : en
Publisher: John Wiley & Sons
Release Date : 2025-07-23
Automated Machine Learning And Industrial Applications written by E. Gangadevi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-23 with Computers categories.
The book provides a comprehensive understanding of Automated Machine Learning’s transformative potential across various industries, empowering users to seamlessly implement advanced machine learning solutions without needing extensive expertise. Automated Machine Learning (AutoML) is a process to automate the responsibilities of machine learning concepts for real-world problems. The AutoML process is comprised of all steps, beginning with a raw dataset and concluding with the construction of a machine learning model for deployment. The purpose of AutoML is to allow non-experts to work with machine learning models and techniques without requiring much knowledge in machine learning. This advancement enables data scientists to produce the easiest solutions and most accurate results within a short timeframe, allowing them to outperform normal machine learning models. Meta-learning, neural network architecture, and hyperparameter optimization, are applied based on AutoML. Automated Machine Learning and Industrial Applications offers an overview of the basic architecture, evolution, and applications of AutoML. Potential applications in healthcare, banking, agriculture, aerospace, and security are discussed in terms of their frameworks, implementation, and evaluation. This book also explores the AutoML ecosystem, its integration with blockchain, and various open-source tools available on the AutoML platform. It serves as a practical guide for engineers and data scientists, offering valuable insights for decision-makers looking to integrate machine learning into their workflows. Readers will find the book: Aims to explore current trends such as augmented reality, virtual reality, blockchain, open-source platforms, and Industry 4.0; Serves as an effective guide for professionals, researchers, industrialists, data scientists, and application developers; Explores technologies such as IoT, blockchain, artificial intelligence, and robotics, serving as a core guide for undergraduate and postgraduate students. Audience Data and computer scientists, research scholars, professionals, and industrialists interested in technology for Industry 4.0 applications.
Machine Learning Algorithms For Industrial Applications
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Author : Santosh Kumar Das
language : en
Publisher: Springer Nature
Release Date : 2020-07-18
Machine Learning Algorithms For Industrial Applications written by Santosh Kumar Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-18 with Technology & Engineering categories.
This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.
Machine Learning And Artificial Intelligence With Industrial Applications
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Author : Diego Carou
language : en
Publisher: Springer Nature
Release Date : 2022-03-11
Machine Learning And Artificial Intelligence With Industrial Applications written by Diego Carou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Technology & Engineering categories.
This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.
Machine Learning For Industrial Applications
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Author : Kolla Bhanu Prakash
language : en
Publisher: John Wiley & Sons
Release Date : 2024-09-04
Machine Learning For Industrial Applications written by Kolla Bhanu Prakash and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-04 with Computers categories.
The main goal of the book is to provide a comprehensive and accessible guide that empowers readers to understand, apply, and leverage machine learning algorithms and techniques effectively in real-world scenarios. Welcome to the exciting world of machine learning! In recent years, machine learning has rapidly transformed from a niche field within computer science to a fundamental technology shaping various aspects of our lives. Whether you realize it or not, machine learning algorithms are at work behind the scenes, powering recommendation systems, autonomous vehicles, virtual assistants, medical diagnostics, and much more. This book is designed to serve as your comprehensive guide to understanding the principles, algorithms, and applications of machine learning. Whether a student diving into this field for the first time, a seasoned professional looking to broaden your skillset, or an enthusiast eager to explore cutting-edge advancements, this book has something for you. The primary goal of Machine Learning for Industrial Applications is to demystify machine learning and make it accessible to a wide audience. It provides a solid foundation in the fundamental concepts of machine learning, covering both the theoretical underpinnings and practical applications. Whether you’re interested in supervised learning, unsupervised learning, reinforcement learning, or innovative techniques like deep learning, you’ll find comprehensive coverage here. Throughout the book, a hands-on approach is emphasized. As the best way to learn machine learning is by doing, the book includes numerous examples, exercises, and real-world case studies to reinforce your understanding and practical skills. Audience The book will enjoy a wide readership as it will appeal to all researchers, students, and technology enthusiasts wanting a hands-on guide to the new advances in machine learning.
Industrial Applications Of Machine Learning
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Author : Pedro Larrañaga
language : en
Publisher: CRC Press
Release Date : 2018-12-12
Industrial Applications Of Machine Learning written by Pedro Larrañaga and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with Business & Economics categories.
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka
Automated Machine Learning And Industrial Applications
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Author : E. Gangadevi
language : en
Publisher: John Wiley & Sons
Release Date : 2025-09-02
Automated Machine Learning And Industrial Applications written by E. Gangadevi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-02 with Computers categories.
The book provides a comprehensive understanding of Automated Machine Learning’s transformative potential across various industries, empowering users to seamlessly implement advanced machine learning solutions without needing extensive expertise. Automated Machine Learning (AutoML) is a process to automate the responsibilities of machine learning concepts for real-world problems. The AutoML process is comprised of all steps, beginning with a raw dataset and concluding with the construction of a machine learning model for deployment. The purpose of AutoML is to allow non-experts to work with machine learning models and techniques without requiring much knowledge in machine learning. This advancement enables data scientists to produce the easiest solutions and most accurate results within a short timeframe, allowing them to outperform normal machine learning models. Meta-learning, neural network architecture, and hyperparameter optimization, are applied based on AutoML. Automated Machine Learning and Industrial Applications offers an overview of the basic architecture, evolution, and applications of AutoML. Potential applications in healthcare, banking, agriculture, aerospace, and security are discussed in terms of their frameworks, implementation, and evaluation. This book also explores the AutoML ecosystem, its integration with blockchain, and various open-source tools available on the AutoML platform. It serves as a practical guide for engineers and data scientists, offering valuable insights for decision-makers looking to integrate machine learning into their workflows. Readers will find the book: Aims to explore current trends such as augmented reality, virtual reality, blockchain, open-source platforms, and Industry 4.0; Serves as an effective guide for professionals, researchers, industrialists, data scientists, and application developers; Explores technologies such as IoT, blockchain, artificial intelligence, and robotics, serving as a core guide for undergraduate and postgraduate students. Audience Data and computer scientists, research scholars, professionals, and industrialists interested in technology for Industry 4.0 applications.
Industrial Applications Of Machine Learning
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Author : Pedro Larrañaga
language : en
Publisher: CRC Press
Release Date : 2018-12-12
Industrial Applications Of Machine Learning written by Pedro Larrañaga and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with Business & Economics categories.
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka
Artificial Intelligence Based Solutions For Industrial Applications
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Author : Pooja Jha
language : en
Publisher: CRC Press
Release Date : 2024-11-20
Artificial Intelligence Based Solutions For Industrial Applications written by Pooja Jha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-20 with Computers categories.
Artificial Intelligence based Solutions for Industrial Applications aims to examine the utilization of artificial intelligence (AI) technologies to tackle difficult industrial issues and offers readers a thorough understanding of how these technologies are being employed to address intricate industrial challenges and to stimulate innovation. This book explores the fundamental principles of artificial intelligence (AI) and its practical use in industrial environments. This book improves understanding of core concepts, the present state of the art and real-time implementation of AI in many industrial applications. This book describes the detailed implementation of AI in the industrial sector as well as related case studies for in-depth understanding. Basic concepts, related work reviews, illustrations, empirical results, and tables are integrated within each chapter to give the readers the opportunity to gain maximum knowledge and to easily understand the methodology and results presented. This book introduces a variety of smart algorithms to help in filtering important information and to solve problems in the application domains. Application of machine learning and deep learning in the industry demonstrates the capabilities by which it may be used to solve practical problems in the 'Fourth Industrial Revolution', and it equips readers with the necessary knowledge and tools to design solutions by themselves with the help of theory and practical examples dealt with. The fourth industrial revolution and its consequences on society and organizations are discussed in this book. Features: Detailed understanding of the industrial application of AI. Discussion of core concepts of different machine learning and deep learning techniques such as artificial neural networks, support vector machines, K –nearest neighbour, decision tree, logistic regression, and many more. Detailed study on various industrial applications of machine learning and deep learning in healthcare, education, entertainment, share market, manufacturing, and many more. Case studies on industrial application of AI Summataion of the fourth industrial revolution and its consquences on society and organizations. This book is primarily written for graduate students, engineers, and academic researchers, industrial practitioners, and anyone who wants to optimize production processes, explore AI technology, or stay ahead in the industrial field. It covers the complexities of AI in industrial contexts from core basic understanding to complex implementation.
Deep Learning Techniques For Automation And Industrial Applications
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Author : Pramod Singh Rathore
language : en
Publisher: John Wiley & Sons
Release Date : 2024-06-24
Deep Learning Techniques For Automation And Industrial Applications written by Pramod Singh Rathore and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-24 with Computers categories.
This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. “Deep Learning Techniques for Automation and Industrial Applications” presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful.
Machine Learning Techniques And Industry Applications
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Author : Srivastava, Pramod Kumar
language : en
Publisher: IGI Global
Release Date : 2024-04-16
Machine Learning Techniques And Industry Applications written by Srivastava, Pramod Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-16 with Computers categories.
In today's rapidly evolving world, the exponential growth of data poses a significant challenge. As data volumes increase, traditional methods of analysis and decision-making become inadequate. This surge in data complexity calls for innovative solutions that efficiently extract meaningful insights. Machine learning has emerged as a powerful tool to address this challenge, offering algorithms and techniques to analyze large datasets and uncover hidden patterns, trends, and correlations. Machine Learning Techniques and Industry Applications demystifies machine learning through detailed explanations, examples, and case studies, making it accessible to a broad audience. Whether you're a student, researcher, or practitioner, this book equips you with the knowledge and skills needed to harness the power of machine learning to address diverse challenges. From e-government to healthcare, cyber-physical systems to agriculture, this book explores how machine learning can drive innovation and sustainable development.