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#497: Outlier Detection with Python

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Manage episode 472621615 series 83399
Content provided by Michael Kennedy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Michael Kennedy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Have you ever wondered why certain data points stand out so dramatically? They might hold the key to everything from fraud detection to groundbreaking discoveries. This week on Talk Python to Me, we dive into the world of outlier detection with Python with Brett Kennedy. You'll learn how outliers can signal errors, highlight novel insights, or even reveal hidden patterns lurking in the data you thought you understood. We'll explore fresh research developments, practical use cases, and how outlier detection compares to other core data science tasks like prediction and clustering. If you're ready to spot those game-changing anomalies in your own projects, stay tuned.
Discount code for Outlier Detection in Python book: talkpython45 (45% off, no expiration date).
Episode sponsors
Posit
Python in Production
Talk Python Courses

Links from the show

Data-morph: github.com
PyOD: github.com
Prophet: github.com
Outlier Detection in Python Book: manning.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy
  continue reading

542 episodes

#497: Outlier Detection with Python

Talk Python To Me

5,692 subscribers

published

iconShare
 
Manage episode 472621615 series 83399
Content provided by Michael Kennedy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Michael Kennedy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Have you ever wondered why certain data points stand out so dramatically? They might hold the key to everything from fraud detection to groundbreaking discoveries. This week on Talk Python to Me, we dive into the world of outlier detection with Python with Brett Kennedy. You'll learn how outliers can signal errors, highlight novel insights, or even reveal hidden patterns lurking in the data you thought you understood. We'll explore fresh research developments, practical use cases, and how outlier detection compares to other core data science tasks like prediction and clustering. If you're ready to spot those game-changing anomalies in your own projects, stay tuned.
Discount code for Outlier Detection in Python book: talkpython45 (45% off, no expiration date).
Episode sponsors
Posit
Python in Production
Talk Python Courses

Links from the show

Data-morph: github.com
PyOD: github.com
Prophet: github.com
Outlier Detection in Python Book: manning.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy
  continue reading

542 episodes

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