preface.tex

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Repository:
\href{https://github.com/ENSYSTRA/short-term-forecasting}{ENSYSTRA/short-term-forecasting}

Short-term forecasting of electricity generation, demand and prices
using machine learning {[}WIP{]}.

Copyright (C) 2019 \href{mailto:nmstreethran@gmail.com}{Nithiya
Streethran}.

Permission is granted to copy, distribute and/or modify this document
under the terms of the \href{https://www.gnu.org/licenses/fdl-1.3}{GNU
Free Documentation License}, Version 1.3 or any later version published
by the Free Software Foundation; with no Invariant Sections, no
Front-Cover Texts, and no Back-Cover Texts. A copy of the license is
included in the section entitled ``GNU Free Documentation License''.

Content sources have been attributed where appropriate. Images are
licensed under the
\href{https://creativecommons.org/licenses/by-sa/4.0/}{Creative Commons
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)} license, where
the image source has not been specified.

This work is part of Nithiya Streethran's research as Early-Stage
Researcher (ESR) 9 of the \href{https://ensystra.eu/}{ENSYSTRA - ENergy
SYStems in TRAnsition} Innovative Training Network, based at the
\href{https://www.uis.no/}{University of Stavanger}. ENSYSTRA is funded
by the European Union's Horizon 2020 research and innovation programme
under the Marie Skłodowska-Curie grant agreement No: 765515.