9780136556619

Artificial Intelligence for Business

by
  • ISBN13:

    9780136556619

  • ISBN10:

    0136556612

  • Edition: 1st
  • Format: Paperback
  • Copyright: 2020-07-31
  • Publisher: Pearson FT Press
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Summary

Millions of non-technical professionals and leaders want to understand Artificial Intelligence (AI) and Machine Learning (ML) — whether to improve their businesses, be more effective citizens, consumers or policymakers, or just out of sheer curiosity. Until now, most books on the subject have either been too complicated and mathematical, or have simply avoided the big picture by focusing on the use of specific software libraries. In Artificial Intelligence for Business , Doug Rose bridges the gap, offering today’s most accessible and useful introduction to AI and ML technologies — and what they can and can’t do. 

Rose begins by tracing AI’s evolution from the early 1950s to the present, illuminating core ideas that still drive its development. Next, he explores recent innovations that have reinvigorated the field by providing the “big data” that makes machine learning so powerful – innovations such as GPS, social media and electronic transactions. Finally, he explains how today’s machines learn by combining powerful processing, advanced algorithms, and artificial neural networks that mimic the human brain.

Throughout, he illustrates key concepts with practical examples that help you connect AI, ML, and neural networks to specific problems and solutions. Step by step, he systematically demystifies these powerful technologies, removing the fear, bewilderment, and advanced math — so you can understand the new possibilities they create, and start using them.

Author Biography

Doug Rose (Atlanta, GA Area) specializes in organizational coaching, training, and change management. He's worked over twenty years transforming organizations with technology and training. Rose has helped several Fortune® 500 clients optimize business processes and improve productivity and delivery. He also teaches at the University of Chicago, Syracuse University, Emory University, and the University of Virginia.

Table of Contents

PART I: THINKING MACHINES: AN OVERVIEW OF ARTIFICIAL INTELLIGENCE
1. What Is Artificial Intelligence?
2. The Rise of Machine Learning
3. Zeroing in on the Best Approach
4. Common AI Applications
5. Putting AI to Work on Big Data
6. Weighing Your Options

PART II: MACHINE LEARNING
7. What Is Machine Learning?
8. Different Ways a Machine Learns
9. Popular Machine Learning Algorithms
10. Applying Machine Learning Algorithms
11. Words of Advice

PART III: ARTIFICIAL NEURAL NETWORKS
12. What Are Artificial Neural Networks?
13. Artificial Neural Networks in Action
14. Letting Your Network Learn
15. Using Neural Networks to Classify or Cluster
16. Key Challenges

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