maikejulie / internIntroML

Slides and materials for an ML introduction for GFDL interns, summer 2020.

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Into to parameter estimation and model choice for summer interns at GFDL

As data volumes grow along with the need to recognize emergent structures efficiently, methods from Machine Learning such as unsupervised learning present an increasingly important tool.

Using unsupervised learning can be an incredibly powerful tool, but should be applied with care. This tutorial uses k-means as a machine learning method to demonstrate the importance of critical model evaluation.

The tutorial accompanies lecture material, and the intended learning outcome is to enable optimal parameter selection.

To launch the Binder and interactively play with the material:

Click the "Launch Binder" button below and wait while the repository starts.

What we will have done is create an online environment where you can execute code by pressing "shift+return" in one of the code cells. If you are on a phone, press the "play" button next to the code cell.

Binder

Today also: https://tinyurl.com/internintroGFDL

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Slides and materials for an ML introduction for GFDL interns, summer 2020.


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