For Your Ears Only: Personalizing Spotify Home with Machine Learning
This article is based on the keynote given by Tony Jebara at TensorFlow World in Santa Clara, California, October 2019. [...]
This article is based on the keynote given by Tony Jebara at TensorFlow World in Santa Clara, California, October 2019. [...]
When Spotify launched in 2008 in Sweden, and in 2011 in the United States, people were amazed that they could access almost the world’s entire music catalog [...]
How do you cut iOS app build times by 50%? Patrick Balestra, an engineer at Spotify, explains how his team [...]
Introduction Large-scale data processing is a critical component of Spotify’s business model. It drives music recommendations, artist payouts based on [...]
Spotify presented its first Machine Learning Day at Spotify headquarters in Stockholm on Monday 9th July to coincide with the International Conference on Machine Learning [...]
We are happy to announce the first Spotify Machine Learning Day taking place Monday, July 9th, 2018, 9:30 AM – 5:30 PM at Spotify, Regeringsgatan 19, Stockholm, Sweden [...]
In this part we’ll take a closer look at Scio, including basic concepts, its unique features, and concrete use cases here at Spotify [...]
Changing an engineering culture is one of the biggest challenges for any organization. It requires challenging an existing way of working, and introducing compelling improvements [...]
This is the first part of a 2 part blog series. In this series we will talk about Scio, a Scala API for Apache Beam and Google Cloud Dataflow, and [...]
What’s your name and where are you from? My name is Charlie and I come from the US and grew [...]
Every day, Spotify users are generating more than 100 billion events. Every event is being generated as a response to [...]
Five years ago, music personalization at Spotify was a tiny team. The team read papers, developed models, wrote data pipelines [...]
This is part three of a three-part series on how we created a career path framework for the individual contributors [...]
This is part two of a three part series on how we created a technical career path for individuals at [...]
Foreword: This post was initiated by Andy Park, former agile coach here at Spotify. For years we’ve been experimenting with how to do “big [...]
At Spotify we have have over 60 million active users who have access to a vast music catalog of over 30 million [...]
Spotify has built several real-time pipelines using Apache Storm for use cases like ad targeting, music recommendation, and data visualization. Each of these [...]
I’m currently on parental leave, which is something that leaves very little time for any concentrated work effort because your [...]
At the heart of Spotify lives a massive and growing data-set. Most data is user-centric and allows us to provide [...]
As we all know, Hadoop is great and here at Spotify we are big fans of it. We use it [...]
The most frequent question we heard at PyCon this weekend, was how do we use Python at Spotify. Hopefully this post answers [...]
backend infrastructure at Spotify. Our backend infrastructure is very much work in progress – in some areas we have come [...]