This project is a part of a Kaggle competition. More information can be found here.

The purpose of this project is to create an algorithmn to identify metastatic cancer in small image patches taken from larger digital pathology scans.

• Inferential Statistics
• Machine Learning
• Data Visualization
• Predictive Modeling

• Python
• Pandas
• Pytorch

• data exploration/descriptive statistics
• data processing/cleaning
• statistical modeling
• writeup/reporting

1. Clone this repo (for help see this tutorial).

2. Raw Data is being kept on kaggle. The size of the data is approximetely 7.7GB.

   If using offline data mention that and how they may obtain the data from the froup)

3. Data processing/transformation scripts are being kept [here](Repo folder containing data processing scripts/notebooks)

4. etc...

5. Follow setup [instructions](Link to file)

• Notebook/Markdown/Slide Deck Title
• Notebook/Markdown/Slide DeckTitle