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Time Series Forecasting in Python
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Time Series Forecasting in Python
by Marco Peixeiro
Time Series Forecasting in Python
inside front cover
Time Series Forecasting in Python
Copyright
dedication
contents
front matter
Part 1. Time waits for no one
1 Understanding time series forecasting
2 A naive prediction of the future
3 Going on a random walk
Part 2. Forecasting with statistical models
4 Modeling a moving average process
5 Modeling an autoregressive process
6 Modeling complex time series
7 Forecasting non-stationary time series
8 Accounting for seasonality
9 Adding external variables to our model
10 Forecasting multiple time series
11 Capstone: Forecasting the number of antidiabetic drug prescriptions in Australia
Part 3. Large-scale forecasting with deep learning
12 Introducing deep learning for time series forecasting
13 Data windowing and creating baselines for deep learning
14 Baby steps with deep learning
15 Remembering the past with LSTM
16 Filtering a time series with CNN
17 Using predictions to make more predictions
18 Capstone: Forecasting the electric power consumption of a household
Part 4. Automating forecasting at scale
19 Automating time series forecasting with Prophet
20 Capstone: Forecasting the monthly average retail price of steak in Canada
21 Going above and beyond
Appendix. Installation instructions
index
inside back cover
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