This is simply a personal library of annotated snippets in Juptyer Notebooks documenting how to "do" certain things in TensorFlow. Simple things, like loading a graph or using batch normalization. Most everything here is adapted from or outright copied from Aurélien Géron, whose fantastic book Hands-On Machine Learnign with Scikit-Learn and Tensorflow I am currently working through. Géron already has all of the code and examples for the book hosted in Notebooks in a github repository, but I also make it a point to try recreating exercises on my own to get it to stick. Moreover, Géron organizes his code by chapter, which makes perfect sense, but I find it hard sometimes to revisit old notebooks (which tend to be quite large) and look up something I forgot how to do. Hence, here I have things broken down "by task" into much smaller notebooks.
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