The Model Complexity Myth
Published September 11, 2015
|
30 min
    Download
    Add to queue
    Copy URL
    Show notes

    There's an old adage which says you cannot fit a model which has more parameters than you have data. While this is often the case, it's not a universal truth. Today's guest Jake VanderPlas explains this topic in detail and provides some excellent examples of when it holds and doesn't. Some excellent visuals articulating the points can be found on Jake's blog Pythonic Perambulations, specifically on his post The Model Complexity Myth.

    We also touch on Jake's work as an astronomer, his noteworthy open source contributions, and forthcoming book (currently available in an Early Edition) Python Data Science Handbook.

      15
      15
        0:00:00 / 0:00:00