Invited talk at Amazon Web Services

By | July 9, 2019

I was recently invited to give a talk at AWS in Berlin. I presented the current work on temporal and cross-temporal hierarchical forecasting. My view is that there is a lot of potential for these approaches to augment existing forecasting processes with relative ease.

Considering the wider forecasting problem, we do not forecast for the sake of forecasting, but to support decisions, with different planning horizons, objectives and information base. These approaches permit merging all these views to achieve aligned decision making, while at the same time improving forecast accuracy. On a personal note, it is nice to see that industry is nowadays very fast at considering/adopting new research. Creating in-house teams with forecasting expertise offers tremendous opportunities to companies to capitalise on innovations in research and the open source community that most researches contribute to. If you are not familiar with the research follow the links above to find out more about them.

On another note, if you are not familiar with the forecasting work of AWS, I will point you to their new open source library for forecasting with deep learning: gluonts. I had the chance to discuss with the team some of the internal workings of the library and they have put together a very interesting and useful tool. I hope to find the time to try it some more myself and I will post my results and thoughts here. A word of caution (this is something that the team at AWS also repeat themselves quite often): deep learning is not the solution for all the problems, but has a lot of potential when the data permit. If you deal with limited sales data and only a few time series, perhaps the humble exponential smoothing is still a very good contender. But otherwise, there are a lot of innovations in neural networks to make them a worthy contender for forecasting. Nonetheless, irrespectively of your views on deep learning and forecasting hats off to AWS for contributing back to the research and open source community.

Finally, many thanks to Tim Januschowski for the invitation and hosting me!


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  1. Pingback: Nikolaos Kourentzes – Forecasting

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