Amelia & Filip — How Pandora Deploys ML Models into Production

Gradient Dissent: Conversations on AI

English - July 01, 2021 19:00 - 40 minutes - 37.4 MB
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Previous Episode: OctoML CEO Luis Ceze on accelerating machine learning systems

Next Episode: How Pandora deploys machine learning models into production with Amelia and Filip

Amelia and Filip give insights into the recommender systems powering Pandora, from developing models to balancing effectiveness and efficiency in production.

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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/

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⏳ 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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