Authors:
- Provides the link between theory and practical, real-world machine learning implementations at an industrialized level
- Supplies a series of advanced practical examples of the autonomous transformational disruptors you can generate with machine learning and use as case studies for your future projects
- Prepares you to gain an advantage from an unfavorable shift in the employment market as autonomous transformational disruptors unavoidably are altering the future job market
- Gives you the information you need to improve your skills to transform data into business insights and to successfully survive the fourth industrial revolution
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (15 chapters)
-
Front Matter
-
Back Matter
About this book
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
Keywords
- Machine learning
- Big data
- Artificial Intelligence
- AI
- Data lake
- Supervised learning
- Data science
- Unsupervised learning
- Reinforcement learning
- Evolutionary computing
- Mechatronics
- Robotics revolution
- Autonomous robotics
- Machine learning in Education
- Virtual reality
- Augmented reality
- Data Science
- Data Engineering
- AR
Authors and Affiliations
-
West Kilbride, UK
Andreas François Vermeulen
About the author
Andreas François Vermeulen is Chief Data Scientist and Solutions Delivery Manager at Sopra-Steria and he serves as part-time doctoral researcher and senior research project advisor at University of St. Andrews on future concepts in health care systems, Internet of Things (IoT) sensors, massive distributed computing, mechatronics, at-scale data lake technology, data science, business intelligence (BI), and deep machine learning in health informatics.
Andre maintains and incubates the Rapid Information Factory data processing framework. He is active in developing next-generation data processing frameworks and mechatronics engineering with over 36 years of global experience in complex data processing, software development, and system architecture. He is an expert data scientist, doctoral trainer, corporate consultant, and speaker/author/columnist on data science, business intelligence, machine learning, decision science, data engineering, distributed computing, and at-scale data lakes. He has expert-level industrial experience in various areas (finance, telecommunication, manufacturing, government service, public safety and health informatics). Andre received his bachelor's degree from North West University at Potchefstroom, his Master of Business Administration (MBA) at University of Manchester, his Master of Business Intelligence and Data Science degree at University of Dundee, and his Doctor of Philosophy at University of St. Andrews.Bibliographic Information
Book Title: Industrial Machine Learning
Book Subtitle: Using Artificial Intelligence as a Transformational Disruptor
Authors: Andreas François Vermeulen
DOI: https://doi.org/10.1007/978-1-4842-5316-8
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Andreas Fran�ois Vermeulen 2020
Softcover ISBN: 978-1-4842-5315-1Published: 01 December 2019
eBook ISBN: 978-1-4842-5316-8Published: 30 November 2019
Edition Number: 1
Number of Pages: XXIII, 637
Number of Illustrations: 300 b/w illustrations
Topics: Artificial Intelligence, Big Data