Space Science with Python - AI 1-6: SVM Grid Search
GitHub Link of today's session: https://github.com/ThomasAlbin/Astron...
-- Space Science with Python - AI 1-6: SVM Grid Search --
Last time we trained a naive Support Vector Machine for a binary classification problem: distinguishing between "X" and "Non-X" asteroid spectra. We used some simple guesses to get a rather good classification performance.
Today we will cover a Grid Search Method in Scikit-Learn to find better parameters for our SVM classifier. However, Scikit-Learn provides an extensive list of parameter search methods that cannot be covered by a single tutorial video.
Next session: Using Keras to create a neural network classifier!
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How to setup a local dev environment: • Space Science with Python - Part 2: Setup ...
Scikit-Learn (Hyper-Parameter Tuning): https://scikit-learn.org/stable/modul...
Scikit-Learn (Metrics / Scoring): https://scikit-learn.org/stable/modul...
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Content
0:00 Introduction + Scikit-Learn
2:33 Python - Getting Started
3:48 Python - Setting up Grid Search & Scaler
7:33 Python - Instantiate & fit Grid Search
11:03 Python - Our best SVM classifier
19:05 Summary & Outlook
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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