Comments (2)
This tutorial may provide a good template.
from climate_learn.
Rather than using a Conv2D layer for the CNN part of the model we may want to explore using a Cropping3D layer instead.
from climate_learn.
Related Issues (17)
- Add model fits/tests for non-linear tendency variables
- Score models (train/test) for features: [Q, PRECL] and labels: [SHFLX, LHFLX]
- Add documentation describing the approach and methodology
- Create PBS script for batch processing on UMichigan cluster (flux)
- Multiple input files support
- Create simple CNN with Keras
- Update scaling approach in order to scale each feature/label separately
- Add batching in order to allow for different fit and predict inputs
- Create a Pipeline for managing machine learning workflow HOT 3
- Develop a simple RNN/LSTM model using Keras HOT 1
- incorporate apricot for feature selection/dataset reduction
- NetCDF output of target variables predicted by the ML-based model
- Add a simple function that splits data for training/testing based on hemisphere
- Add unit tests for model.py
- Add support for CI (continuous integration) with Travis
- Score models (train/test) for features: [PS, T, U, and V] and label: PTTEND HOT 1
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from climate_learn.