Industrial Machine Learning

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Industrial Machine Learning

Andreas François Vermeulen
Industrial Machine Learning Book PDF

Author : Andreas François Vermeulen
Publisher : Apress
Page : 652 pages
File Size : 46,9 Mb
Release : 2019-11-30
Category : Computers
ISBN : 9781484253168

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Industrial Machine Learning by Andreas François Vermeulen Pdf

Understand the industrialization of machine learning (ML) and take the first steps toward identifying and generating the transformational disruptors of artificial intelligence (AI). You will learn to apply ML to data lakes in various industries, supplying data professionals with the advanced skills required to handle the future of data engineering and data science. Data lakes currently generated by worldwide industrialized business activities are projected to reach 35 zettabytes (ZB) as the Fourth Industrial Revolution produces an exponential increase of volume, velocity, variety, variability, veracity, visualization, and value. Industrialization of ML evolves from AI and studying pattern recognition against the increasingly unstructured resource stored in data lakes. Industrial Machine Learning supplies advanced, yet practical examples in different industries, including finance, public safety, health care, transportation, manufactory, supply chain, 3D printing, education, research, and data science. The book covers: supervised learning, unsupervised learning, reinforcement learning, evolutionary computing principles, soft robotics disruptors, and hard robotics disruptors. What You Will Learn Generate and identify transformational disruptors of artificial intelligence (AI) Understand the field of machine learning (ML) and apply it to handle big data and process the data lakes in your environment Hone the skills required to handle the future of data engineering and data science Who This Book Is For Intermediate to expert level professionals in the fields of data science, data engineering, machine learning, and data management

Industrial Applications of Machine Learning

Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza
Industrial Applications of Machine Learning Book PDF

Author : Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza
Publisher : CRC Press
Page : 336 pages
File Size : 51,7 Mb
Release : 2018-12-12
Category : Business & Economics
ISBN : 9781351128377

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Industrial Applications of Machine Learning by Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza Pdf

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

Machine Learning in Industry

Shubhabrata Datta,J. Paulo Davim
Machine Learning in Industry Book PDF

Author : Shubhabrata Datta,J. Paulo Davim
Publisher : Springer Nature
Page : 202 pages
File Size : 50,5 Mb
Release : 2021-07-24
Category : Technology & Engineering
ISBN : 9783030758479

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Machine Learning in Industry by Shubhabrata Datta,J. Paulo Davim Pdf

This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.

Machine Learning Algorithms for Industrial Applications

Santosh Kumar Das,Shom Prasad Das,Nilanjan Dey,Aboul-Ella Hassanien
Machine Learning Algorithms for Industrial Applications Book PDF

Author : Santosh Kumar Das,Shom Prasad Das,Nilanjan Dey,Aboul-Ella Hassanien
Publisher : Springer Nature
Page : 321 pages
File Size : 40,8 Mb
Release : 2020-07-18
Category : Technology & Engineering
ISBN : 9783030506414

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Machine Learning Algorithms for Industrial Applications by Santosh Kumar Das,Shom Prasad Das,Nilanjan Dey,Aboul-Ella Hassanien Pdf

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.

Industrial Applications of Machine Learning

Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza
Industrial Applications of Machine Learning Book PDF

Author : Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza
Publisher : CRC Press
Page : 336 pages
File Size : 51,5 Mb
Release : 2018-12-12
Category : Business & Economics
ISBN : 9781351128360

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Industrial Applications of Machine Learning by Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza Pdf

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

Smart Agents for the Industry 4.0

Max Hoffmann
Smart Agents for the Industry 4 0 Book PDF

Author : Max Hoffmann
Publisher : Springer Nature
Page : 318 pages
File Size : 55,7 Mb
Release : 2019-09-11
Category : Computers
ISBN : 9783658277420

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Smart Agents for the Industry 4.0 by Max Hoffmann Pdf

Max Hoffmann describes the realization of a framework that enables autonomous decision-making in industrial manufacturing processes by means of multi-agent systems and the OPC UA meta-modeling standard. The integration of communication patterns and SOA with grown manufacturing systems enables an upgrade of legacy environments in terms of Industry 4.0 related technologies. The added value of the derived solutions are validated through an industrial use case and verified by the development of a demonstrator that includes elements of self-optimization through Machine Learning and communication with high-level planning systems such as ERP. About the Author: Dr.-Ing. Max Hoffmann is a scientific researcher at the Institute of Information Management in Mechanical Engineering, RWTH Aachen University, Germany, and leads the group “Industrial Big Data”. His research emphasizes on production optimization by means of data integration through interoperability and communication standards for industrial manufacturing and integrated analysis by using Machine Learning and stream-based information processing.

Reinforcement Learning

Phil Winder Ph.D.
Reinforcement Learning Book PDF

Author : Phil Winder Ph.D.
Publisher : "O'Reilly Media, Inc."
Page : 517 pages
File Size : 43,5 Mb
Release : 2020-11-06
Category : Computers
ISBN : 9781492072348

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Reinforcement Learning by Phil Winder Ph.D. Pdf

Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcement and enable a machine to learn by itself. Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; doesn't shy away from math and expects familiarity with ML. Learn what RL is and how the algorithms help solve problems Become grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learning Dive deep into a range of value and policy gradient methods Apply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learning Understand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and more Get practical examples through the accompanying website

Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems

Rui Yang,Maiying Zhong
Machine Learning Based Fault Diagnosis for Industrial Engineering Systems Book PDF

Author : Rui Yang,Maiying Zhong
Publisher : CRC Press
Page : 87 pages
File Size : 47,8 Mb
Release : 2022-06-16
Category : Technology & Engineering
ISBN : 9781000594935

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Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems by Rui Yang,Maiying Zhong Pdf

This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.

Intelligent Systems and Machine Learning for Industry

P. R Anisha,C. Kishor Kumar Reddy,Nhu Gia Nguyen,Megha Bhushan,Ashok Kumar,Marlia Mohd Hanafiah
Intelligent Systems and Machine Learning for Industry Book PDF

Author : P. R Anisha,C. Kishor Kumar Reddy,Nhu Gia Nguyen,Megha Bhushan,Ashok Kumar,Marlia Mohd Hanafiah
Publisher : CRC Press
Page : 362 pages
File Size : 54,7 Mb
Release : 2022-12-21
Category : Computers
ISBN : 9781000828832

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Intelligent Systems and Machine Learning for Industry by P. R Anisha,C. Kishor Kumar Reddy,Nhu Gia Nguyen,Megha Bhushan,Ashok Kumar,Marlia Mohd Hanafiah Pdf

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: • Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. • Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. • Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. • Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. • Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. • Discusses a systematic and exhaustive analysis of intelligent software effort estimation models. It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Machine Learning and Artificial Intelligence with Industrial Applications

Diego Carou,Antonio Sartal,J. Paulo Davim
Machine Learning and Artificial Intelligence with Industrial Applications Book PDF

Author : Diego Carou,Antonio Sartal,J. Paulo Davim
Publisher : Springer Nature
Page : 216 pages
File Size : 42,8 Mb
Release : 2022-03-11
Category : Technology & Engineering
ISBN : 9783030910068

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Machine Learning and Artificial Intelligence with Industrial Applications by Diego Carou,Antonio Sartal,J. Paulo Davim Pdf

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 and Data Science in the Power Generation Industry

Patrick Bangert
Machine Learning and Data Science in the Power Generation Industry Book PDF

Author : Patrick Bangert
Publisher : Elsevier
Page : 276 pages
File Size : 42,7 Mb
Release : 2021-01-14
Category : Technology & Engineering
ISBN : 9780128226001

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Machine Learning and Data Science in the Power Generation Industry by Patrick Bangert Pdf

Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. Provides best practices on how to design and set up ML projects in power systems, including all nontechnological aspects necessary to be successful Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how the data must be prepared for them Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems Accompanied by numerous supporting real-world case studies, providing practical evidence of both best practices and potential pitfalls

HR Without People?

Anthony R. Wheeler,M. Ronald Buckley
HR Without People Book PDF

Author : Anthony R. Wheeler,M. Ronald Buckley
Publisher : Emerald Group Publishing
Page : 133 pages
File Size : 55,8 Mb
Release : 2021-08-09
Category : Business & Economics
ISBN : 9781801170390

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HR Without People? by Anthony R. Wheeler,M. Ronald Buckley Pdf

HR Without People? is a stimulating and confrontational challenge to conventional thinking on this people-centric profession’s role in the future of work.

Control Charts and Machine Learning for Anomaly Detection in Manufacturing

Kim Phuc Tran
Control Charts and Machine Learning for Anomaly Detection in Manufacturing Book PDF

Author : Kim Phuc Tran
Publisher : Springer
Page : 0 pages
File Size : 47,9 Mb
Release : 2022-08-31
Category : Technology & Engineering
ISBN : 3030838218

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Control Charts and Machine Learning for Anomaly Detection in Manufacturing by Kim Phuc Tran Pdf

This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process. By approaching anomaly detection using both statistics and machine learning, the book promotes interdisciplinary cooperation between the research communities, to jointly develop new anomaly detection approaches that are more suitable for the 4.0 Industrial Revolution. The book provides ready-to-use algorithms and parameter sheets, enabling readers to design advanced control charts and machine learning-based approaches for anomaly detection in manufacturing. Case studies are introduced in each chapter to help practitioners easily apply these tools to real-world manufacturing processes. The book is of interest to researchers, industrial experts, and postgraduate students in the fields of industrial engineering, automation, statistical learning, and manufacturing industries.

Cancer Prediction for Industrial IoT 4.0

Meenu Gupta,Rachna Jain,Arun Solanki,Fadi Al-Turjman
Cancer Prediction for Industrial IoT 4 0 Book PDF

Author : Meenu Gupta,Rachna Jain,Arun Solanki,Fadi Al-Turjman
Publisher : CRC Press
Page : 202 pages
File Size : 42,7 Mb
Release : 2021-12-31
Category : Computers
ISBN : 9781000508666

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Cancer Prediction for Industrial IoT 4.0 by Meenu Gupta,Rachna Jain,Arun Solanki,Fadi Al-Turjman Pdf

Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines. Features • Covers the fundamentals, history, reality and challenges of cancer • Presents concepts and analysis of different cancers in humans • Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer • Offers real-world examples of cancer prediction • Reviews strategies and tools used in cancer prediction • Explores the future prospects in cancer prediction and treatment Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions. This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry

Stephanie K. Ashenden
The Era of Artificial Intelligence Machine Learning and Data Science in the Pharmaceutical Industry Book PDF

Author : Stephanie K. Ashenden
Publisher : Academic Press
Page : 266 pages
File Size : 51,8 Mb
Release : 2021-04-23
Category : Computers
ISBN : 9780128204498

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The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry by Stephanie K. Ashenden Pdf

The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide