nelmsal / Spring2022-Week6

MUSA 650: Machine Learning in Remote Sensing

Week6: ML using satellite images

This repository contains:

• [HW1 Review]
• ML evaluation metrics
• Nested_CV_Example
• SVM Brief Presentation
• 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/1tFpnkiVi6N9AktfZ-3Y6mKCVtIDN_QDq?usp=sharing

Sharing link for datasets: https://drive.google.com/drive/folders/10HpS26ZPhUXaJ8FrEMuUD01-aSjoTfC7?usp=sharing

Steps for replicating "PrjA1_DSTL_ImgChannelsMasks.ipynb" :

• Copy shared datasets in a google drive folder
• 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 (!!! you may need to edit the path to data)

Article of the week:

Very interesting article, please check: https://hub.packtpub.com/8-machine-learning-best-practices/