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#497: Outlier Detection with Python

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Manage episode 472624571 series 2453836
Indhold leveret af Michael Kennedy. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Michael Kennedy eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.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.
Episode sponsors
Posit
Python in Production
Talk Python Courses

Links from the show

Data-morph: github.com
PyOD: github.com
Prophet: github.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

507 episoder

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#497: Outlier Detection with Python

Talk Python To Me

36 subscribers

published

iconDel
 
Manage episode 472624571 series 2453836
Indhold leveret af Michael Kennedy. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Michael Kennedy eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.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.
Episode sponsors
Posit
Python in Production
Talk Python Courses

Links from the show

Data-morph: github.com
PyOD: github.com
Prophet: github.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

507 episoder

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