MetOffice / MetOffice/ai4c_hackathon
time series tutorial example
- Dominant language
- Jupyter Notebook
- Stars
- 2
- Forks
- 3
- Avg merge
- 1m
- Merged PRs (30d)
- 1
Description
Create an example of an RNN or similar for the tutorial, using the Jena dataset.
Useful material
- Kaggle dataset https://www.kaggle.com/datasets/mnassrib/jena-climate/code
- Example code https://www.kaggle.com/code/rahulkate173/jena-climate-dataset-lstm-gru
- https://lightning.ai/lightning-ai/environments/time-series-forecasting-with-pytorch-lightning?section=featured
- https://www.geeksforgeeks.org/data-analysis/time-series-forecasting-using-pytorch/
- https://machinelearningmastery.com/lstm-for-time-series-prediction-in-pytorch/
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by reviewing the linked Jena climate dataset and the referenced RNN, LSTM, GRU, and PyTorch tutorial material. Create a tutorial example using the Jena dataset and an RNN or similar model; done means the example is usable as tutorial material.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100