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"Powering Spotify's Audio Personalization Platform" by Josh Baer (Strange Loop 2022)
Learn how Spotify's audio personalization platform uses machine learning to suggest music, albums, and more, featuring multiple loops, experimentation, and scalable infrastructure.
- Spotify’s audio personalization platform uses machine learning to suggest music tracks, albums, and more.
- The platform is powered by multiple loops, including problem understanding, feature engineering, model training, and deployment.
- Each loop involves experimentation, A/B testing, and iteration to improve the model.
- The company uses tools like ML Home, TFX, and Kubeflow to streamline the machine learning process.
- The platform incorporates various models, including collaborative filtering and recommendation models.
- The company has a large team of data scientists and engineers working on the platform.
- Spotify’s machine learning infrastructure is designed to be scalable and efficient, with automated workflows and batch processing.
- The company uses various metrics to measure the performance of the platform, including click-through rates and play rates.
- The platform is used to power features like Discover Weekly and Release Radar.
- Spotify has a large dataset of user interactions, including listening habits and ratings.
- The company uses this data to train machine learning models and improve the platform’s recommendations.
- The platform is designed to be adaptable and evolvable, with continuous training and development.
- The company uses techniques like TensorFlow Extended and Kubeflow to automate the machine learning process.
- Spotify has a strong focus on autonomy and self-service, with automated workflows and batch processing.
- The platform is used to power features like the Spotify Home page and search results.
- The company uses various techniques to disambiguate artists and improve the accuracy of their recommendations.
- Spotify’s machine learning platform is designed to be scalable and efficient, with automated workflows and batch processing.
- The company uses various metrics to measure the performance of the platform, including click-through rates and play rates.
- The platform is used to power features like Discover Weekly and Release Radar.
- Spotify has a large team of data scientists and engineers working on the platform.