fpp3-python-readalong

These notes are a Python-centered read-along of the excellent Forecasting: Principles and Practice by Rob J Hyndman and George Athanasopoulos [1].

Please find the table of contents on Jupyter nbviewer.

[1] Hyndman, R.J., & Athanasopoulos, G. (2019) Forecasting: principles and practice, 3rd edition, OTexts: Melbourne, Australia. OTexts.com/fpp3. Accessed on 2020-07-20.

Name		Name	Last commit message	Last commit date
.gitignore		.gitignore
00-Preface-to-this-readalong.ipynb		00-Preface-to-this-readalong.ipynb
02-Time-series-graphics.ipynb		02-Time-series-graphics.ipynb
03-Time-series-decomposition.ipynb		03-Time-series-decomposition.ipynb
04-Time-series-features.ipynb		04-Time-series-features.ipynb
05-The-forecasters-toolbox.ipynb		05-The-forecasters-toolbox.ipynb
06-Judgmental-forecasts.ipynb		06-Judgmental-forecasts.ipynb
07-Time-series-regression-models.ipynb		07-Time-series-regression-models.ipynb
08-Exponential-smoothing.ipynb		08-Exponential-smoothing.ipynb
09-ARIMA-models.ipynb		09-ARIMA-models.ipynb
10-Dynamic-regression-models.ipynb		10-Dynamic-regression-models.ipynb
Contents.ipynb		Contents.ipynb
R-export-datasets.ipynb		R-export-datasets.ipynb
README.md		README.md
__init__.py		__init__.py
utils.py		utils.py

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