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You're reading from  R Deep Learning Essentials. - Second Edition

Product typeBook
Published inAug 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781788992893
Edition2nd Edition
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Authors (2):
Mark Hodnett
Mark Hodnett
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Mark Hodnett

Mark Hodnett is a data scientist with over 20 years of industry experience in software development, business intelligence systems, and data science. He has worked in a variety of industries, including CRM systems, retail loyalty, IoT systems, and accountancy. He holds a master's in data science and an MBA. He works in Cork, Ireland, as a senior data scientist with AltViz.
Read more about Mark Hodnett

Joshua F. Wiley
Joshua F. Wiley
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Joshua F. Wiley

Joshua F. Wiley is a lecturer at Monash University, conducting quantitative research on sleep, stress, and health. He earned his Ph.D. from the University of California, Los Angeles and completed postdoctoral training in primary care and prevention. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. He develops or co-develops a number of R packages including Varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.
Read more about Joshua F. Wiley

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TensorFlow models

In this section, we will use TensorFlow to build some machine learning models. First, we will build a simple linear regression model and then a convolutional neural network model, similar to what we have seen in Chapter 5, Image Classification Using Convolutional Neural Networks.

The following code loads the TensorFlow library. We can confirm it loaded successfully by setting and accessing a constant string value:

> library(tensorflow)

# confirm that TensorFlow library has loaded
> sess=tf$Session()
> hello_world <- tf$constant('Hello world from TensorFlow')
> sess$run(hello_world)
b'Hello world from TensorFlow'

Linear regression using TensorFlow

In this first Tensorflow example...

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R Deep Learning Essentials. - Second Edition
Published in: Aug 2018Publisher: PacktISBN-13: 9781788992893

Authors (2)

author image
Mark Hodnett

Mark Hodnett is a data scientist with over 20 years of industry experience in software development, business intelligence systems, and data science. He has worked in a variety of industries, including CRM systems, retail loyalty, IoT systems, and accountancy. He holds a master's in data science and an MBA. He works in Cork, Ireland, as a senior data scientist with AltViz.
Read more about Mark Hodnett

author image
Joshua F. Wiley

Joshua F. Wiley is a lecturer at Monash University, conducting quantitative research on sleep, stress, and health. He earned his Ph.D. from the University of California, Los Angeles and completed postdoctoral training in primary care and prevention. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. He develops or co-develops a number of R packages including Varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.
Read more about Joshua F. Wiley