Deep Learning Image Classification with Keras and Shiny

February 19, 2018
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[This article was first published on Jasmine Dumas' R Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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I have to admit my initial thoughts of deep learning were pessimistic and in order to not succumb to impostor syndrome, I put off learning any new techniques in the growing sub field of machine learning, until recently. After attending & speaking at Data Day Texas and listening to Lukas Biewald’s Keynote titled: Deep Learning in the Real World, I began to see through the complexities of Deep Learning and understand the real world applications. My favorite example from the keynote was Coca Cola deploying a deep learning model to easily capture under the cap promotional codes. I left the conference with some initial ideas about detecting deer in my backyard using a web cam and running a image classification algorithm as my first step into learning by doing.

For this image classification project I leveraged a pre-trained model from the R interface to Keras, that had been previously trained on a similar task. This enabled me to prototype something quickly and cheaply in a weekend and wrap the code as an interactive web app with a shiny flexdashboard. Here is the link to the shiny app which enables you to upload a image and return the top 3 predicted classes for that image: https://jasminedumas.shinyapps.io/image_clf/ and a preview of the app in action below.

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