AI Simplified: Rookie Mistakes

New to the world of AI and machine learning? Nobody is an expert right out of the gate. With that in mind, John Boersma, Director of Education at DataRobot, shares his list of the top three rookie mistakes in machine learning for our AI Simplified series.

 

These are the key mistakes John highlights:

  1. Not understanding your data: If you don’t understand your data, you’ll overlook missing data values and inconsistencies in data formats. Also, you may miss out on opportunities to improve your data set so better models can be built.

  2. Limiting yourself to  one or a couple modeling approaches: You can miss out on models that better suit your data and business problem if you only use your preferred methods.

  3. Not thinking about implementation: Ask yourself questions like:
    “Are there automated processes that will need to change?”
    “Is training required?”

Watch John’s full AI Simplified video below and learn more about rookie mistakes, as well as how to successfully avoid them:

At DataRobot, we value AI and machine learning education. To learn more about John’s work and our course offerings, visit DataRobot University.

What else can you learn from AI Simplified? Check out the DataRobot YouTube channel for every video in the series. 

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