Deep Learning for Recommender Systems Justin Basilico & Yves - - PowerPoint PPT Presentation

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Deep Learning for Recommender Systems Justin Basilico & Yves - - PowerPoint PPT Presentation

Deep Learning for Recommender Systems Justin Basilico & Yves Raimond March 28, 2018 GPU Technology Conference @JustinBasilico @moustaki The value of recommendations A few seconds to find something great to watch Can only show a


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Deep Learning for Recommender Systems

Justin Basilico & Yves Raimond

March 28, 2018

GPU Technology Conference @JustinBasilico @moustaki

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The value of recommendations

  • A few seconds to find something

great to watch…

  • Can only show a few titles
  • Enjoyment directly impacts

customer satisfaction

  • Generates over $1B per year of

Netflix revenue

  • How? Personalize everything
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Deep learning for recommendations: a first try

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1 1 1 1 1 1 1 1 1 Users Items

Traditional Recommendation Setup

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U

R V

A Matrix Factorization view

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U

A Feed-Forward Network view

V

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U

A (deeper) feed-forward view

V

Mean squared loss

?

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A quick & dirty experiment

■ ■ ○ ■ ■ ■ ■ ■

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GPU vs. CPU

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What’s going on?

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Conclusion?

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Breaking the ‘traditional’ recsys setup

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Alternative data

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Content-based side information

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Metadata-based side information

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YouTube Recommendations

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Alternative models

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Restricted Boltzmann Machines

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Auto-encoders

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(*)2Vec

  • prod2vec

(Skip-gram)

user2vec

(Continuous Bag of Words)

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Wide + Deep models

  • [Cheng et. al., 2016]
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Alternative framings

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Sequence prediction

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Contextual sequence prediction

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Contextual sequence data

2017-12-10 15:40:22 2017-12-23 19:32:10 2017-12-24 12:05:53 2017-12-27 22:40:22 2017-12-29 19:39:36 2017-12-30 20:42:13 Context Action Sequence per user

?

Time

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Time-sensitive sequence prediction

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Other framings

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Conclusion

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Takeaways

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More Resources

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Thank you.

@JustinBasilico @moustaki

Justin Basilico & Yves Raimond

Yes, we’re hiring...