This tutorial will be a hands-on tour of
Verde, a
Python package for
processing and
gridding geophysical/geospatial data with a twist of
machine learning.
BEFORE THE TUTORIAL: Please go to
github.com/fatiando/transform2020 and follow the setup instructions. There is also information on where to ask questions and what is going to happen in the tutorial.
We'll start with a real dataset and work our way towards producing one or more gridded products. The way there will take us through:
- Loading some data
- Generating and handling coordinates and projections (using pyproj)
- Splitting training and testing data for validation
- Data decimation with blocked means/medians to avoid aliasing
- 2D trend estimation
- Gridding with bi-harmonic splines
- Combining everything into a data processing pipeline
- Cross-validation of data distrubuted spatially on the Earth (including parallel execution)
UPDATE: Given the size of the tutorial, this will mainly be some live coding to showcase what Verde can do with participants following along. There will be some short exercises that can be done individually after the tutorial is finished. We will finish a bit earlier than the scheduled time to leave room for more questions/chat at the end.