Training your TensorFlow models in the cloud

April 25, 2018 Andrie de Vries
Abstract
TensorFlow is an open-source software library for numerical computation using data flow graphs. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. In this talk we’ll cover the R interface to TensorFlow, a suite of packages that provide high-level interfaces to both deep learning models (Keras) and standard regression and classification models (Estimators), as well as tools for cloud training, experiment management, and production deployment.

About the Author

Andrie de Vries

Andrie is a Solutions Engineer at RStudio, where he helps customers and partner with their deployment of R as an analytical environment. He started using R in 2009 for market research statistics and joined Revolution analytics in 2013, where he helped customers with their challenges in adopting R for machine learning. After the acquisition of Revolution analytics by Microsoft in 2015, he worked with customers on their implementation of neural network and machine learning projects. He joined RStudio during 2017. He is co-author of "R for dummies" and is a regular speaker at industry conferences.

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