/Image_Classification_using_Deep_Learning

In this project, you'll train an image classifier to recognize different species of flowers. You can imagine using something like this in a phone app that tells you the name of the flower your camera is looking at. In practice you'd train this classifier, then export it for use in your application. We'll be using this dataset from Oxford of 102 flower categories, you can see a few examples below.

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Intro to Machine Learning - TensorFlow Project

Project code for Udacity's Intro to Machine Learning with TensorFlow Nanodegree program. In this project, you will first develop code for an image classifier built with TensorFlow, then you will convert it into a command line application.

In order to complete this project, you will need to use the GPU enabled workspaces within the classroom. The files are all available here for your convenience, but running on your local CPU will likely not work well.

You should also only enable the GPU when you need it. If you are not using the GPU, please disable it so you do not run out of time!

Data

The data for this project is quite large - in fact, it is so large you cannot upload it onto Github. If you would like the data for this project, you will want download it from the workspace in the classroom.
Though actually completing the project is likely not possible on your local unless you have a GPU. You will be training using 102 different types of flowers, where there ~20 images per flower to train on.
Then you will use your trained classifier to see if you can predict the type for new images of the flowers.