Personalizing the infinite jukebox : ML and the TensorFlow ecosystem at Spotify / Josh Baer, Keshi Dai.

Format:

Video

Author/Creator:

Baer, Josh, on-screen presenter.

Contributor:

Dai, Keshi, on-screen presenter.

Language:

English

Subjects (All):

Machine learning.

Artificial intelligence.

Physical Description:

1 online resource (1 streaming video file (39 min., 40 sec.)) : digital, sound, color

Other Title:

ML and the TensorFlow ecosystem at Spotify

Place of Publication:

[Place of publication not identified] : O'Reilly Media, 2020.

Summary:

"When Spotify launched in 2008, the lucky first launch countries rejoiced at the prospect of an almost infinite jukebox at their fingertips. In the 10+ years that followed, the product evolved quite a bit from something that required you to know exactly what you wanted to listen to before you listened to the product today that offers countless recommendations and a personalized experience. It's no surprise that ML has had a prominent role in that evolution. Josh Baer and Keshi Dai explain how Spotify applied ML to personalize its product and discuss the historical challenges of bringing ML products to market. You'll learn how Spotify uses TensorFlow and, especially, the TFX family of products as a "paved" workflow and how this has improved the ability for product teams to leverage ML in their work. You'll also examine the current state of the ML platform at Spotify and the open challenges the company faces."--Resource description page.

Participant:

Presenter, Josh Baer, Keshi Dai.

Notes:

Title from resource description page (viewed July 22, 2020).

OCLC:

1176539716