A Human’s Guide to Machine Learning Projects
With various stakeholders, differing background knowledge among team members, and administrative hurdles, many projects die before they have a chance to fly. The solution to this problem is to build a solid project foundation from the very first stages to set yourself up for success. But how do you do that?
In this guide, you’ll learn:
- The process RapidMiner uses across different industries & applications to ensure ML projects start off on the right foot
- How to respond to the most common objections about starting a machine learning project
- The basics of CRISP-DM and why it’s the most widely used analytics process in the world
- Why your focus should be on business outcomes, and how to keep that focus in mind throughout the project
- What you should consider when preparing your data
Getting a machine learning project off the ground is hard— this guide will help make it easier.
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