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You're reading from  Forecasting Time Series Data with Facebook Prophet

Product typeBook
Published inMar 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781800568532
Edition1st Edition
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Greg Rafferty
Greg Rafferty
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Greg Rafferty

Greg Rafferty is a data scientist in San Francisco, California. With over a decade of experience, he has worked with many of the top firms in tech, including Google, Facebook, and IBM. Greg has been an instructor in business analytics on Coursera and has led face-to-face workshops with industry professionals in data science and analytics. With both an MBA and a degree in engineering, he is able to work across the spectrum of data science and communicate with both technical experts and non-technical consumers of data alike.
Read more about Greg Rafferty

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Parallelizing cross-validation

There is a lot of iteration going on during cross-validation and these are tasks that can be parallelized to speed things up. All you need to do to take advantage of this is use the parallel keyword. There are four options you may choose: None, 'processes', 'threads', or 'dask':

df_cv = cross_validation(model,
                         horizon='90 days',
                         period='30 days',
                         initial='730 days',
              ...
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Forecasting Time Series Data with Facebook Prophet
Published in: Mar 2021Publisher: PacktISBN-13: 9781800568532

Author (1)

author image
Greg Rafferty

Greg Rafferty is a data scientist in San Francisco, California. With over a decade of experience, he has worked with many of the top firms in tech, including Google, Facebook, and IBM. Greg has been an instructor in business analytics on Coursera and has led face-to-face workshops with industry professionals in data science and analytics. With both an MBA and a degree in engineering, he is able to work across the spectrum of data science and communicate with both technical experts and non-technical consumers of data alike.
Read more about Greg Rafferty