Reader small image

You're reading from  Machine Learning for Time-Series with Python

Product typeBook
Published inOct 2021
PublisherPackt
ISBN-139781801819626
Edition1st Edition
Right arrow
Author (1)
Ben Auffarth
Ben Auffarth
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

Right arrow

Summary

In this chapter, we've introduced time-series, the history of research into time-series, and Python for time-series.

We started with a definition of time-series and its main properties. We then looked at the history of the study of time-series in different scientific disciplines, such as demography and genetics, astronomy, economics, meteorology, medicine, and applied statistics.

Then, we went over the capabilities of Python for time-series and why Python is the go-to language for doing machine learning with time-series. Finally, I described how to install and use Python for time-series analysis and machine learning, and we covered some of the basics of Python as relevant to time-series and machine learning.

In the next chapter, we'll look at time-series analysis with Python.

lock icon
The rest of the page is locked
Previous PageNext Chapter
You have been reading a chapter from
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