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Published inOct 2021
PublisherPackt
ISBN-139781801819626
Edition1st Edition
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Ben Auffarth
Ben Auffarth
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Ben Auffarth

Ben Auffarth is a full-stack data scientist with more than 15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds and thousands of transactions per day, and trained language models on a large corpus of text documents. He co-founded and is the former president of Data Science Speakers, London.
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Python Exercise

Let's put into practice what we've learned in this chapter so far. We'll be doing a model in Prophet, a Markov Switching model, a Fuzzy time-series model, and a BSTS model.

Let's get started with Prophet!

Prophet

First, let's make sure we have everything installed that we need. Let's quickly install the required libraries. We can do this from the terminal (or similarly from the Anaconda navigator):

pip install -U pandas-datareader plotly

You'll need a recent version of pandas-datareader, otherwise you might get a RemoteDataError.

We'll use the Prophet model through Facebook's Prophet library. Let's install it:

pip install prophet

Once this is done, we are set to go.

In this example, we'll use the daily Yahoo closing stock values in this chapter that we used in several examples in Chapter 7, Machine Learning Models for Time-Series.

To recap, we can download the daily Yahoo...

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Machine Learning for Time-Series with Python
Published in: Oct 2021Publisher: PacktISBN-13: 9781801819626

Author (1)

author image
Ben Auffarth

Ben Auffarth is a full-stack data scientist with more than 15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds and thousands of transactions per day, and trained language models on a large corpus of text documents. He co-founded and is the former president of Data Science Speakers, London.
Read more about Ben Auffarth