Space Science with Python - Cassini #4: Machine Learning based calibration
Repository: https://github.com/ThomasAlbin/Astron...
After taking a look at the already existing calibration functions, today, we will try to create a first "machine learning toy model" to calibrate CDA. For this purpose, we use Tensorflow and its high-level API keras.
In the following videos we will refine our calibration attempt to create a production-ready model for future scientific analysis.
Credit - Thumbnail: NASA/JPL-Caltech
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Content
0:00 Introduction
1:32 Coding - Intro
2:21 Coding - Read in the data
3:07 Coding - Plotting the calibration data in 3D
6:59 Coding - Data preparation
9:12 Coding - Machine Learning Training
13:35 Coding - Solution space in 3D
17:06 Summary & Outlook
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How to setup a local dev environment: • Space Science with Python - Part 2: Setup ...
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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:
Mastodon: https://astrodon.social/@ThomasAlbin
Twitter: / mrastrothomas
Reddit: / mrastrothomas
GitHub: https://github.com/ThomasAlbin
Or drop a comment!
Talk to you later,
Thomas
#space #science #Python #tutorial #datascience #cassini #nasa #saturn #ml #ai #machinelearning #deeplearning