Machine Learning resource: Chris Albon’s Code Snippets and Flashcards

Jessica YungEducation, Machine LearningLeave a Comment

I was looking for code to implement early stopping in Keras today and came across Chris Albon’s website. You may know Chris as a host of Partially Derivative, a podcast about data science.

Chris has posted many snippets of commented recipe-like code to do simple things on his website. These range from ways to preprocess images, text and dates such as creating rolling time windows to machine learning methods like hyperparameter tuning to programming essentials like writing a unit test. The explanations I have read so far have been clear and concise. I have bookmarked this as a reference and recommend you have a look too – this will likely save you time programming at some point.

Here is part of his page on Early Stopping, which basically means you stop training your model when e.g. your validation loss increases. This snippet is preceded by code that loads data and sets up a neural network, giving a complete but easy-to-understand example.


From .

Chris also has a set of fun pictorial machine learning flashcards. Here’s one example:


Flashcard on Support Vectors by Chris Albon.

You can view the flashcards on Twitter or buy them for USD12 on his website.

On a related note, I am creating a set of flashcards based on Ian Goodfellow, Yoshua Bengio and Aaron Courville’s Deep Learning book (live on GitHub). Am quite excited because flashcards have helped me learn material really well, and I hope this project will help people starting out improve their knowledge of machine learning concepts. Let me know what you think! 🙂

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