January 2018
Intermediate to advanced
474 pages
10h 23m
English
Content preview from Mastering TensorFlow 1.x
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Summary
In this chapter, we learned how to use TensorFlow Core, TensorFlow Estimators, and Keras packages in R to build and train machine learning models. We provided a walkthrough of the MNIST examples from RStudio and provided links for further documentation of the TensorFlow and Keras R packages. We also learned how to use the visualization tool TensorBoard from within R. We also introduced a new tool from R Studio, tfruns, which allows you to create reports for multiple runs, analyze and compare them, and save them locally or publish them.
The ability to work directly in R is useful because plenty of production data science and machine learning code is written using R, and now you can integrate TensorFlow into the same codebase and run ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.