April 2018
Beginner to intermediate
500 pages
11h 26m
English
book
Hands-On Machine Learning on Google Cloud Platform
by Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier, Bryan Fry, Antonio Gulli
Content preview from Hands-On Machine Learning on Google Cloud Platform
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Analyzing a time series dataset
To see how to perform a seasonality removal operation on a time series, we will use a dataset on monthly milk production (pounds per cow; January 1962 – December 1975). Here is some useful information about this dataset:
- Units: Pounds per cow
- Dataset metrics: 168 fact values in one time series
- Time granularity: Month
- Time range: January 1962 – December 1975
- Source: Time Series Data Library
The Time Series Data Library (TSDL) was created by Rob Hyndman, a professor of statistics at Monash University, Australia.
The data is available in a .csv file named milk-production-pounds.csv. To start, let's see how to import the data into Python and then how to display it to identify the possible presence of seasonality. ...
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