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Overview of Netflix and Spotify like recommendation engines

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Manage episode 243278356 series 2550866
Contenuto fornito da Sanket Gupta. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Sanket Gupta o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode, we cover the two main types of recommendation engines used at companies like Netflix and Spotify.

1) Content based recommendation systems use the genres or tags of each product to find other similar products to recommend to users.
2) Collaborative filtering based recommendation systems use user activity and user ratings on the website to recommend products.

We go through the pros and cons of each, the challenges, how do companies like Netflix and Spotify scale their recommendation engines for millions of users and more!

My code in the Github repo which implements these concepts from scratch using MovieLens dataset.

Links:
1) Youtube talk by Xavier Amatriain from Netflix
2) Youtube talk on "Machine Learning & Big Data for Music Discovery presented by Spotify"
3) Youtube tutorial by Luis Serrano on how Netflix recommends movies

#netflix #spotify #movielens #recommendations #recommendation-engines

--- Send in a voice message: https://podcasters.spotify.com/pod/show/the-data-life-podcast/message Support this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support
  continue reading

27 episodi

Artwork
iconCondividi
 
Manage episode 243278356 series 2550866
Contenuto fornito da Sanket Gupta. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Sanket Gupta o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode, we cover the two main types of recommendation engines used at companies like Netflix and Spotify.

1) Content based recommendation systems use the genres or tags of each product to find other similar products to recommend to users.
2) Collaborative filtering based recommendation systems use user activity and user ratings on the website to recommend products.

We go through the pros and cons of each, the challenges, how do companies like Netflix and Spotify scale their recommendation engines for millions of users and more!

My code in the Github repo which implements these concepts from scratch using MovieLens dataset.

Links:
1) Youtube talk by Xavier Amatriain from Netflix
2) Youtube talk on "Machine Learning & Big Data for Music Discovery presented by Spotify"
3) Youtube tutorial by Luis Serrano on how Netflix recommends movies

#netflix #spotify #movielens #recommendations #recommendation-engines

--- Send in a voice message: https://podcasters.spotify.com/pod/show/the-data-life-podcast/message Support this podcast: https://podcasters.spotify.com/pod/show/the-data-life-podcast/support
  continue reading

27 episodi

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