Issue-409 Add support for datasets that can't fit in memory

[jasminerienecker]

As described in this issue: https://github.com/Nixtla/neuralforecast/issues/409

We assume the dataset is split across multiple parquet files - each parquet file corresponds to a single timeseries which is represented as a pandas dataframe. This PR creates a new Dataset class where the getitem method reads the parquet file corresponding to that index, and the from_data_directory() method replicates the from_df() method.

I have added a test to end of core.ipynb that checks the forecasts using this distributed dataset are the same as when the dataset is directly passed in as a pandas dataframe.

[review-notebook-app[bot]]

Check out this pull request on 

See visual diffs & provide feedback on Jupyter Notebooks.

---

Powered by ReviewNB

[CLAassistant]

All committers have signed the CLA.

[jmoralez]

Thanks a lot for your contribution @jasminerienecker, I left some comments.

[jmoralez]

Thanks a lot for working through the changes! I left some more enhancement ideas

[jmoralez]

Thanks a lot @jasminerienecker! I think after these changes it'll be ready