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SkillsCast

How to Improve your Recommender System with Deep Learning: A Use Case

29th April 2017 in London at CodeNode

There are 19 other SkillsCasts available from Data Science Festival 2017

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Deep learning is without a doubt among the hottest topics in data science today. Computers are now more powerful than ever, and as a result, deep learning has been applied successfully by academics during the past few years. However, it is still unclear how difficult it is for businesses to apply it. We want to go beyond the buzzword and share concrete examples of where deep learning has been successfully used.

Recommender systems are paramount for e-business companies. There is an increasing need to take into account all user information to provide the best, most tailored products. One important element is the content that the user actually sees: the visual of the product.

In this talk, you will discover how Dataiku improved an e-business vacation retailer recommender system using the content of images. You'll explore how to leverage open datasets and pre-trained deep learning models to derive user preference information. This transfer learning approach enables companies to use state-of-the-art machine learning methods without having deep learning expertise.

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How to Improve your Recommender System with Deep Learning: A Use Case

Alexandre Hubert

Alexandre Hubert has been a data scientist at Dataiku for more than two years. He works on several bank use cases as loan delinquency for leasing and refactoring institutions but also marketing use cases for retailers. Before that, he worked as a trader in the city of London.

SkillsCast

Please log in to watch this conference skillscast.

Https s3.amazonaws.com prod.tracker2 resource 41088130 skillsmatter conference skillscast o9nohu

Deep learning is without a doubt among the hottest topics in data science today. Computers are now more powerful than ever, and as a result, deep learning has been applied successfully by academics during the past few years. However, it is still unclear how difficult it is for businesses to apply it. We want to go beyond the buzzword and share concrete examples of where deep learning has been successfully used.

Recommender systems are paramount for e-business companies. There is an increasing need to take into account all user information to provide the best, most tailored products. One important element is the content that the user actually sees: the visual of the product.

In this talk, you will discover how Dataiku improved an e-business vacation retailer recommender system using the content of images. You'll explore how to leverage open datasets and pre-trained deep learning models to derive user preference information. This transfer learning approach enables companies to use state-of-the-art machine learning methods without having deep learning expertise.

YOU MAY ALSO LIKE:

About the Speaker

How to Improve your Recommender System with Deep Learning: A Use Case

Alexandre Hubert

Alexandre Hubert has been a data scientist at Dataiku for more than two years. He works on several bank use cases as loan delinquency for leasing and refactoring institutions but also marketing use cases for retailers. Before that, he worked as a trader in the city of London.

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