This is the final project of AI Programming with Python Nanodegree program by Udacity
Going forward, AI algorithms will be incorporated into more and more everyday applications. For example, you might want to include an image classifier in a smart phone app. To do this, you'd use a deep learning model trained on hundreds of thousands of images as part of the overall application architecture. A large part of software development in the future will be using these types of models as common parts of applications.
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 of 102 flower categories.
The project is broken down into multiple steps:
- Load and preprocess the image dataset
- Train the image classifier on your dataset
- Use the trained classifier to predict image content
The project contains 3 types of source files:
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html source file (Image Classifier Project.html)
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jupyter source file (Image Classifier Project.ipynb)
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python source file (util.py, train.py, predict.py)
Verified Certification:
You can check the certificate in the folder (Udacity_Certificate.pdf)
Packages:
As you go through the jupyter source file(jupyternotebook) you will find what you need to import, make sure to import the Packages.