Episode
Improve The Success Rate Of Your Machine Learning Projects With bizML
- Podcast
- AI Engineering Podcast
- Published
- Feb 18, 2024
- Duration seconds
- 3022
- Processing state
failed
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Summary
Summary Machine learning is a powerful set of technologies, holding the potential to dramatically transform businesses across industries. Unfortunately, the implementation of ML projects often fail to achieve their intended goals. This failure is due to a lack of collaboration and investment across technological and organizational boundaries. To help improve the success rate of machine learning projects Eric Siegel developed the six step bizML framework, outlining the process to ensure that everyone understands the whole process of ML deployment. In this episode he shares the principles and promise of that framework and his motivation for encapsulating it in his book "The AI Playbook". Announcements Hello and welcome to the Machine Learning Podcast, the podcast about machine learning and how to bring it from idea to delivery. Your host is Tobias Macey and today I'm interviewing Eric Siegel about how the bizML approach can help improve the success rate of your ML projects Interview Introduction How did you get involved in machine learning? Can you describe what bizML is and the story behind it? What are the key aspects of this approach that are different from the "industry standard" lifecycle of an ML project? What are the elements of your personal experience as an ML consultant that helped you develop the tenets of bizML? Who are the personas that need to be involved in an ML project to increase the likelihood of success? Who do you find to be best suited to "own" or "lead" the process? What are the organizational patterns that might hinder the work of delivering on the goals of an ML initiative? What are some of the misconceptions about the work involved in/capabilities of an ML model that you commonly encounter? What is your main goal in writing your book…