You should be comfortable with R and RStudio and have some knowledge of college-level mathematics (calculus and linear algebra). Working knowledge of basic machine learning algorithms for classification, regression problems, and clustering might be helpful, but it is not strictly required.
To get the most out of this book
Download the example code files
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You can download the code files by following these steps:
- Log in or register at www.packtpub.com.
- Select the SUPPORT tab.
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The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/R-Deep-Learning-Projects. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!
Conventions used
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Similarly, for the second sample, (a "0"), we run:"
A block of code is set as follows:
> for (i in 1:16) {
+ outputData <- as.array
(executor$ref.outputs$activation15_output)[,,i,1]
+ image(outputData, xaxt='n', yaxt='n',
col=grey.colors(255)
+ )
+ }
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
library(R6)
logit <- function(x){
1/(1+exp(-x))
}
Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Once logged in, click on Create New App."