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 reader
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.
Table of Contents:
1. Introduction
2. How to use AI in your business
3. Choosing your first AI project
4. Linking business and technology
5. What is an ML pipeline, and how does it affect an AI project?
6. Analyzing an ML pipeline
7. Guiding an AI project to success
8. AI trends that may affect you
