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Industrial Digital Transformation

Industrial Digital Transformation

By : Shyam Varan Nath, Dunkin, Chowdhary, Patel
4.8 (17)
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Industrial Digital Transformation

Industrial Digital Transformation

4.8 (17)
By: Shyam Varan Nath, Dunkin, Chowdhary, Patel

Overview of this book

Digital transformation requires the ability to identify opportunities across industries and apply the right technologies and tools to achieve results. This book is divided into two parts with the first covering what digital transformation is and why it is important. The second part focuses on how digital transformation works. After an introduction to digital transformation, you will explore the transformation journey in logical steps and understand how to build business cases and create productivity benefit statements. Next, you’ll delve into advanced topics relating to overcoming various challenges. Later, the book will take you through case studies in both private and public sector organizations. You’ll explore private sector organizations such as industrial and hi-tech manufacturing in detail and get to grips with public sector organizations by learning how transformation can be achieved on a global scale and how the resident experience can be improved. In addition to this, you will understand the role of artificial intelligence, machine learning and deep learning in digital transformation. Finally, you’ll discover how to create a playbook that can ensure success in digital transformation. By the end of this book, you’ll be well-versed with industrial digital transformation and be able to apply your skills in the real world.
Table of Contents (15 chapters)
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1
Section 1: The "Why" of Digital Transformation
6
Section 2: The "How" of Digital Transformation

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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Industrial Digital Transformation
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