Artwork

Contenido proporcionado por Michael Kennedy. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Michael Kennedy o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
Player FM : aplicación de podcast
¡Desconecta con la aplicación Player FM !

#497: Outlier Detection with Python

55:22
 
Compartir
 

Manage episode 472624571 series 2453836
Contenido proporcionado por Michael Kennedy. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Michael Kennedy o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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 book: TPkennedy3 (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
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

508 episodios

Artwork

#497: Outlier Detection with Python

Talk Python To Me

36 subscribers

published

iconCompartir
 
Manage episode 472624571 series 2453836
Contenido proporcionado por Michael Kennedy. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Michael Kennedy o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.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 book: TPkennedy3 (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
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

508 episodios

Todos los episodios

×
 
Loading …

Bienvenido a Player FM!

Player FM está escaneando la web en busca de podcasts de alta calidad para que los disfrutes en este momento. Es la mejor aplicación de podcast y funciona en Android, iPhone y la web. Regístrate para sincronizar suscripciones a través de dispositivos.

 

Guia de referencia rapida

Escucha este programa mientras exploras
Reproducir