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A Python implementation of Seasonal and Trend decomposition using Loess (STL) for time series data.
An experiment in labeling images found in Tweets.
Forked from tw-ddis/Data-Science-45min-Intros
Materials for our team teaching+learning sessions around CS, ML, stats, and related data science topics. Intended to take ~45 minutes, mostly in narrative IPython notebooks.
Code and notes from using scikit-learn on the MNIST digits dataset. For more of a narrative on this project, see the article:
things that make the computer work
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I've attempted to be more explicit and consistent with the language used to explain and differentiate between the two CLI flags:
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