Space Science with Python - AI 1-13: Gaussian Mixture Model
GitHub Link of today's session: https://github.com/ThomasAlbin/Astron...
Viewers! Our Asteroid Reflectance Spectra is coming to an end. This video and the next one will determine, whether an un-supervised algorithm (in this case: a Gaussian Mixture Model - GMM) will sufficiently cluster or spectra data.
In fact we won't use the spectra per se, but their low-dimensional representation using the Keras-based Autoencoder we developed last time. Enjoy!
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How to setup a local dev environment: • Space Science with Python - Part 2: Setup ...
Autoencoders: • Space Science with Python - Concepts 4: Au...
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Content
0:00 Introduction / Recap
3:24 Theory - GMM & Bayesian Information Criterion (BIC)
10:47 Cell 11 - Scikit-Learn GMM
11:50 Cell 12 - Plotting the BIC
14:17 Cell 13 - GMM Classes
14:50 Cell 13 - Confusion Matrix (Main Group - GMM Classes)
16:55 Summary & Outlook
17:35 Scikit-Learn: Clustering
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There is a lot to do and to learn and I hope you will join the journey. Meanwhile, if you have questions or ideas, reach out to me via:
Twitter: / mrastrothomas
Reddit: / mrastrothomas
GitHub: https://github.com/ThomasAlbin
Or drop a comment!
Talk to you later,
Thomas