Description
Guest Forward (Say from a CEO/founder of an AI company)
Introduction (Quick overview of what the book will cover, chapter-by-chapter)
Chapter 1: AI Landscape- Look at the growth opportunities and the need for digital transformation. But also highlight the challenges with AI implementations.Chapter 2: Identify The Problem To Be Solved- The problem can be internal (such as with improving operations) or external (helping to provide better customer experiences). This chapter will look at cases where companies have been successful with this. Chapter 3: Data Preparation- This often does not get enough attention. But data preparation is absolutely essential and full of mine fields. There will be a look at how to identify/clean the data, such a with various tools and techniques. This chapter will also describe strategies for data ethics, governance, provenance and compliance. Chapter 4: Building the AI Team- This shows what skillsets are required and how to recruit the right people. There will also be a look at setting up the right incentives, roles and duties. Chapter 5: Creating the Model- This chapter will focus on what algorithms to use, how to select the parameters and how to test/train the models. There will also be coverage on the various types of tools to select and when to create in-house ones. Chapter 6: Deploy The Model- Here there is a look at strategies for having limited releases and rollouts. There will also be a look at different approaches for the design of the UI so as to get better adoption.Chapter 7: Monitoring- This chapter will show how to keep track of the model and know when to make changes/upgrades.Chapter 8: Scaling AI- This has proven to be extremely difficult for organizations. So in this chapter, there will be a look at strategies to show how AI can move the needle.Chapter 9: The Future- Again, there needs to be a different mindset. Thus, for a successful AI implementation, it's important to look at change management strategies. Chapter 10: The Future- This will be a recap of the main takeaways of the book and also a look at major trends with AI.Appendix A: Resources like blogs, videos and websitesAppendix B: AI Tools (TensorFlow, DataRobot, Microsoft AI Builder, etc)Appendix C: AI Glossary
Author: Tom Taulli
Publisher: Apress
Published: 12/29/2020
Pages: 196
Binding Type: Paperback
Weight: 0.66lbs
Size: 9.21h x 6.14w x 0.44d
ISBN13: 9781484263846
ISBN10: 1484263847
BISAC Categories:
- Computers | Artificial Intelligence | General
Introduction (Quick overview of what the book will cover, chapter-by-chapter)
Chapter 1: AI Landscape- Look at the growth opportunities and the need for digital transformation. But also highlight the challenges with AI implementations.Chapter 2: Identify The Problem To Be Solved- The problem can be internal (such as with improving operations) or external (helping to provide better customer experiences). This chapter will look at cases where companies have been successful with this. Chapter 3: Data Preparation- This often does not get enough attention. But data preparation is absolutely essential and full of mine fields. There will be a look at how to identify/clean the data, such a with various tools and techniques. This chapter will also describe strategies for data ethics, governance, provenance and compliance. Chapter 4: Building the AI Team- This shows what skillsets are required and how to recruit the right people. There will also be a look at setting up the right incentives, roles and duties. Chapter 5: Creating the Model- This chapter will focus on what algorithms to use, how to select the parameters and how to test/train the models. There will also be coverage on the various types of tools to select and when to create in-house ones. Chapter 6: Deploy The Model- Here there is a look at strategies for having limited releases and rollouts. There will also be a look at different approaches for the design of the UI so as to get better adoption.Chapter 7: Monitoring- This chapter will show how to keep track of the model and know when to make changes/upgrades.Chapter 8: Scaling AI- This has proven to be extremely difficult for organizations. So in this chapter, there will be a look at strategies to show how AI can move the needle.Chapter 9: The Future- Again, there needs to be a different mindset. Thus, for a successful AI implementation, it's important to look at change management strategies. Chapter 10: The Future- This will be a recap of the main takeaways of the book and also a look at major trends with AI.Appendix A: Resources like blogs, videos and websitesAppendix B: AI Tools (TensorFlow, DataRobot, Microsoft AI Builder, etc)Appendix C: AI Glossary
Author: Tom Taulli
Publisher: Apress
Published: 12/29/2020
Pages: 196
Binding Type: Paperback
Weight: 0.66lbs
Size: 9.21h x 6.14w x 0.44d
ISBN13: 9781484263846
ISBN10: 1484263847
BISAC Categories:
- Computers | Artificial Intelligence | General
About the Author
Tom Taulli has been developing software since the 1980s. In college, he started his first company, which focused on the development of e-learning systems. He created other companies as well, including Hypermart.net that was sold to InfoSpace in 1996. Along the way, Tom has written columns for online publications such as BusinessWeek.com, TechWeb.com, and Bloomberg.com. He also writes posts on Artificial Intelligence for Forbes.com and is the adviser to various companies in the space. You can reach Tom on Twitter (@ttaulli) or through his website (Taulli.com) where he has an online course on AI.