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Machine Learning for Time Series Forecasting with Python
book

Machine Learning for Time Series Forecasting with Python

by Francesca Lazzeri
December 2020
Beginner to intermediate content levelBeginner to intermediate
224 pages
5h 54m
English
Wiley
Content preview from Machine Learning for Time Series Forecasting with Python

References

  1. Bianchi, Filippo Maria, and Enrico Maiorino, Michael Kampffmeyer, Antonello Rizzi, Robert Jenssen. 2018. Recurrent Neural Networks for Short-Term Load Forecasting. Berlin, Germany: Springer.
  2. Brownlee, Jason. 2017. Introduction to Time Series Forecasting With Python - Discover How to Prepare Data and Develop Models to Predict the Future. Machine Learning Mastery. https://machinelearningmastery.com/introduction-to-time-series-forecasting-with-python/.
  3. Che, Zhengping, and Sanjay Purushotham, Kyunghyun Cho, David Sontag, Yan Liu. 2018. “Recurrent Neural Networks for Multivariate Time Series with Missing Values.” Scientific Reports 8. https://doi.org/10.1038/s41598-018-24271-9.
  4. Cheng H., Tan PN., Gao J., Scripps J. 2006. “Multistep-Ahead Time Series Prediction.” In: Ng WK., Kitsuregawa M., Li J., Chang K. (eds) Advances in Knowledge Discovery and Data Mining, PAKDD 2006. Lecture Notes in Computer Science 3918. Berlin, Heidelberg: Springer. https://doi.org/10.1007/11731139_89.
  5. Cho, Kyunghyun, and Bart van Merriënboer, Caglar Gulcehre, Fethi Bougares, Holger Schwenk, Y Bengio. 2014. Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. https://doi.org/10.3115/v1/D14-1179.
  6. Glen, Stephanie. 2014. “Endogenous Variable and Exogenous Variable: Definition and Classifying.” Statistics How To blog. https://www.statisticshowto.com/endogenous-variable/.
  7. Lazzeri, Francesca. 2019a. “3 reasons to add deep learning to your time series toolkit ...
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Publisher Resources

ISBN: 9781119682363Purchase Link