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Industrial Digital Transformation

You're reading from   Industrial Digital Transformation Accelerate digital transformation with business optimization, AI, and Industry 4.0

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800207677
Length 426 pages
Edition 1st Edition
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Authors (4):
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Nital Patel Nital Patel
Author Profile Icon Nital Patel
Nital Patel
Ann Dunkin Ann Dunkin
Author Profile Icon Ann Dunkin
Ann Dunkin
Mahesh Chowdhary Mahesh Chowdhary
Author Profile Icon Mahesh Chowdhary
Mahesh Chowdhary
Shyam Varan Nath Shyam Varan Nath
Author Profile Icon Shyam Varan Nath
Shyam Varan Nath
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: The "Why" of Digital Transformation
2. Chapter 1: Introducing Digital Transformation FREE CHAPTER 3. Chapter 2: Transforming the Culture in an Organization 4. Chapter 3: Emerging Technologies to Accelerate Digital Transformation 5. Chapter 4: Business Drivers for Industrial Digital Transformation 6. Section 2: The "How" of Digital Transformation
7. Chapter 5: Transforming One Industry at a Time 8. Chapter 6: Transforming the Public Sector 9. Chapter 7: The Transformation Ecosystem 10. Chapter 8: Artificial Intelligence in Digital Transformation 11. Chapter 9: Pitfalls to Avoid in the Digital Transformation Journey 12. Chapter 10: Measuring the Value of Transformation 13. Chapter 11: The Blueprint for Success 14. Other Books You May Enjoy

The difference between AI, machine learning, and deep learning

Let's start with definitions of AI, Machine Learning (ML), and deep learning in order to get a better understanding of each of these technologies. Figure 1.4 in Chapter 1, Introducing Digital Transformation, shows different fields of research that fall under AI and the approximate timeframe when they gained popularity.

Artificial intelligence

AI is the field of study and its applications that utilize computers to perform tasks that are generally accomplished with the help of human intelligence. These tasks can include perception using visual, audio, and tactile/haptic inputs, pattern recognition in motion/environmental sensor data, and decision-making.

Machine learning

ML is a subset of AI as a field of study. Algorithms used in ML are trained using large amounts of data tagged with associated and relevant real-world information. ML algorithms are being used in a variety of applications, such as automatic...

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