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Stellar classification using machine learning

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If you have a question about this talk, please contact Chih-Chun Chen.

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Twinkle twinkle little star, how I wonder what you are… This free evening talk will explore Machine Learning applications in astrophysics, using manual star classification techniques as an example.

From the speaker: In my previous life, I was an astronomer and one of the big tasks many PhD students face is manual star classification. But why ask a student to do what a machine should be able to do too? In this talk, I use the spectra (stellar flux vs wavelength) of identified stars to build a classifier which will detect the identity of the stars. Using a very simple non linear SVM , I achieve an 86% accuracy with my model. The next step is to use deep neural nets to achieve a better accuracy.

This talk is part of the Cambridge Coding Academy free tech talks series.

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