Jupyter Digest. - Script Generation from RNNs. If you’ve read the hilarious list of paint names from a neural network and wondering how you might do it yourself, this Notebook provides a walkthrough of the theory and code.
- TensorFlow Book companion notebooks. Manning’s “MEAP” program is great, providing early access to manuscripts as they’re being developed. This Machine Learning with TensorFlow MEAP looks to be a real winner, just based on the companion notebooks. As always with these “in progress” books, though, be sure to check back frequently for updates.
- Delivering Transportation Insights using Jupyter Notebooks, Interactive Dashboards, and Apache Spark. It’s an older case study, but it still checks out. This post from Justin Tyberg at IBM shows how to pull a bunch of open source tools together to analyze data for the swank-sounding “Executive Transportation Group” (via @mikeloukides).
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Notebooks for “Hands-On Machine Learning.” This is a set of notebooks for—you guessed it—doing machine learning in Python with Scikit-Learn and TensorFlow. Another great open Jupyter resource from O’Reilly, and a companion to Hands-On Machine Learning with Scikit-Learn & TensorFlow.
