Amelia & Filip — How Pandora Deploys ML Models into Production
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Amelia and Filip give insights into the recommender systems powering Pandora, from developing models to balancing effectiveness and efficiency in production.

Amelia Nybakke is a Software Engineer at Pandora. Her team is responsible for the production system that serves models to listeners. Filip Korzeniowski is a Senior Scientist at Pandora working on recommender systems. Before that, he was a PhD student working on deep neural networks for acoustic and language modeling applied to musical audio recordings.

Connect with Amelia and Filip: 📍 Amelia's LinkedIn: https://www.linkedin.com/in/amelia-nybakke-60bba5107/ 📍 Filip's LinkedIn: https://www.linkedin.com/in/filip-korzeniowski-28b33815a/

⏳ Timestamps: 0:00 Sneak peek, intro 0:42 What type of ML models are at Pandora? 3:39 What makes two songs similar or not similar? 7:33 Improving models and A/B testing 8:52 Chaining, retraining, versioning, and tracking models 13:29 Useful development tools 15:10 Debugging models 18:28 Communicating progress 20:33 Tuning and improving models 23:08 How Pandora puts models into production 29:45 Bias in ML models 36:01 Repetition vs novelty in recommended songs 38:01 The bottlenecks of deployment

🌟 Transcript: http://wandb.me/gd-amelia-and-filip 🌟

Links: 📍 Amelia's "Women's History Month" playlist: https://www.pandora.com/playlist/PL:1407374934299927:100514833

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