Succeeding with AI video edition

Video description

Chock-full of illuminating examples that will dramatically improve your success with AI projects.
Zarak Mahmud, Techflo

Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It’s filled with practical techniques for running data science programs that ensure they’re cost effective and focused on the right business goals.

about the technology

Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren’t enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you’ll get the results you want.

about the book

Succeeding with AI sets out a framework for planning and running cost-effective, reliable AI projects that produce real business results. This practical guide reveals secrets forged during the author’s experience with dozens of startups, established businesses, and Fortune 500 giants that will help you establish meaningful, achievable goals. In it you’ll master a repeatable process to maximize the return on data-scientist hours and learn to implement effectiveness metrics for keeping projects on track and resistant to calcification.

what's inside

  • Where to invest for maximum payoff
  • How AI projects are different from other software projects
  • Catching early warnings in time to correct course
  • Exercises and examples based on real-world business dilemmas

about the audience

For project and business leadership, result-focused data scientists, and engineering teams. No AI knowledge required.

about the author

Veljko Krunic is a data science consultant, has a computer science PhD, and is a certified Six Sigma Master Black Belt.

If you are starting a new AI project, put all odds on your side by reading this book.
David Paccoud, Bioclinica

A definitive resource for building an AI system idea...and deploying it in production.
Teresa Fontanella De Santis, Accenture

Follow this book’s advice, and you will find your organization "succeeding with AI"!
James J. Byleckie, BH Enterprises

NARRATED BY NATE COLITTO

Table of contents

  1. Chapter 1. Introduction
  2. Chapter 1. AI and the Age of Implementation
  3. Chapter 1. Machine learning from 10,000 feet
  4. Chapter 1. Start by understanding the possible business actions
  5. Chapter 1. AI finds correlations, not causes!
  6. Chapter 1. What is CLUE?
  7. Chapter 1. Exercises
  8. Chapter 2. How to use AI in your business
  9. Chapter 2. How is AI used?
  10. Chapter 2. Making money with AI
  11. Chapter 2. Finding domain actions
  12. Chapter 2. AI as a part of a larger product
  13. Chapter 2. Overview of AI capabilities
  14. Chapter 2. Introducing unicorns
  15. Chapter 2. Exercises
  16. Chapter 3. Choosing your first AI project
  17. Chapter 3. Prioritizing AI projects
  18. Chapter 3. Measuring AI project success with business metrics
  19. Chapter 3. Your first project and first research question
  20. Chapter 3. Pitfalls to avoid
  21. Chapter 3. Using your gut feeling instead of CLUE
  22. Chapter 4. Linking business and technology
  23. Chapter 4. Linking business problems and research questions
  24. Chapter 4. A metric you don’t understand is a poor business metric
  25. Chapter 4. Measuring progress on AI projects
  26. Chapter 4. Linking technical progress with a business metric
  27. Chapter 4. Why is this not taught in college?
  28. Chapter 4. Organizational considerations
  29. Chapter 5. What is an ML pipeline, and how does it affect an AI project?
  30. Chapter 5. Challenges the AI system shares with a traditional software system
  31. Chapter 5. Example of ossification of an ML pipeline
  32. Chapter 5. How to address ossification of the ML pipeline
  33. Chapter 5. Why we need to analyze the ML pipeline
  34. Chapter 5. What’s the role of AI methods?
  35. Chapter 5. Balancing data, AI methods, and infrastructure
  36. Chapter 6. Analyzing an ML pipeline
  37. Chapter 6. Economizing resources: The E part of CLUE
  38. Chapter 6. How to interpret MinMax analysis results
  39. Chapter 6. What if your ML pipeline needs improvement?
  40. Chapter 6. How to perform an analysis of the ML pipeline
  41. Chapter 6. Performing the Max part of MinMax analysis
  42. Chapter 6. Estimates and safety factors in MinMax analysis
  43. Chapter 6. Dealing with complex profit curves
  44. Chapter 6. FAQs about MinMax analysis
  45. Chapter 7. Guiding an AI project to success
  46. Chapter 7. Performing local sensitivity analysis
  47. Chapter 7. We’ve completed CLUE
  48. Chapter 7. Advanced methods for sensitivity analysis
  49. Chapter 7. How to address the interactions between ML pipeline stages
  50. Chapter 7. One common objection you might encounter
  51. Chapter 7. How to analyze the stage that produces data
  52. Chapter 7. How your AI project evolves through time
  53. Chapter 7. Concluding your AI project
  54. Chapter 8. AI trends that may affect you
  55. Chapter 8. AI in physical systems
  56. Chapter 8. IoT devices and AI systems must play well together
  57. Chapter 8. AI doesn’t learn causality, only correlations
  58. Chapter 8. How are AI errors different from human mistakes?
  59. Chapter 8. AutoML is approaching
  60. Chapter 8. Guiding AI to business results
  61. Appendix B. Exercise solutions
  62. Appendix B. Answers to chapter 2 exercises
  63. Appendix B. Answers to chapter 3 exercises
  64. Appendix B. Answers to chapter 6 exercises
  65. Appendix B. Answers to chapter 7 exercises

Product information

  • Title: Succeeding with AI video edition
  • Author(s): Veljko Krunic
  • Release date: March 2020
  • Publisher(s): Manning Publications
  • ISBN: None