Starting the project

For this project, you will work in the Jupyter GPU workspace provided for you. You can also find the notebooks containing the necessary starter code in the workspace.

You may also download all of the files for the project directly from this repo.
This workspace contains:

EDA.ipynb: This is the file you will be performing the EDA.
Build and train model.ipynb: This is the file you will be building and training your model.
Inference.ipynb: This is the file you will be performing clinical workflow integration.
.dcm files: They are the test files to test the clinical workflow integration.
sample_labels.csv: This is the file that should be used to assess images in the pixel-level.
FDA_Submission_Template.md: This is the template for you to create the FDA submission. Please copy the template into your choice of editor. Finish the documentation, save it as a .pdf file, and upload.

Note: The NIH data for EDA and training is mounted in the Udacity Jupyter GPU workspace provided to you along with the code to load the data. Alternatively, you can download the data from the kaggle website and run it locally. You are STRONGLY recommended to complete the project using the Udacity workspace since the data is huge, and you will need GPU to accelerate the training process.

Detailed instruction for this project is provided in this README file.

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