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

Product typeBook
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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Machine learning with time-series

In this section, I'll give an introduction to applications and the main categories of machine learning with time-series.

Machine learning approaches for time-series are crucial in domains such as economics, medicine, meteorology, demography, and many others. Time-Series datasets are ubiquitous and occur in domains as diverse as healthcare, economics, social sciences, Internet-of-Things applications, operations management, digital marketing, cloud infrastructure, the simulation of robotic systems, and others. These datasets are of immense practical importance, as they can be leveraged to forecast and predict the detection of anomalies more effectively, thereby supporting decision making.

The technical applications within machine learning for time-series abound in techniques. A few applications are as follows:

  • Curve fitting
  • Regression
  • Classification
  • Forecasting
  • Segmentation/clustering
  • Anomaly detection...
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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