hzqianzhuang/Week4

MUSA 650: Machine Learning in Remote Sensing

Week4: Data Representation and Unsupervised Learning

This repository contains:

• Introduction to satellite image analysis with Python, DSTL challenge
• A first machine learning application using Satellite imaging, DSTL challenge
• Image clustering, Philadelphia

Access to colab notebooks and datasets:

You can run this week's satellite imaging notebooks on "Google Colab"

Sharing link for Jupyter notebooks: https://drive.google.com/drive/folders/1br4IZGPH-ybkQvQWVHBIdorbwzqrmFxn?usp=sharing

Sharing link for datasets: https://drive.google.com/drive/folders/15dLkXRSt1iFGsBDc2zw_w3QkMhjXE2OE?usp=sharing

Steps for replicating "PrjA1_DSTL_ImgChannelsMasks.ipynb" :

• Copy shared datasets in a google drive folder named as "PrjData"
• Go to Google Colab, copy the Jupyter notebook there (or copy it in your Google Drive, click on it and select "open in Colab")
• Run the notebook