Combining online and offline data provides a great opportunity to generalize detailed information of identified online customers to the entire customer database. This session presents a practical example on how we create recipe recommendations to all our customers by applying machine learning techniques to a combination of online and offline data. We will also present a brief overview of our technical environment for data processing, machine learning and output delivery to various channels.
Key Points:
- A novel approach to provide recipe recommendations for people with no browsing history
- Practical example of using machine learning algorithms on large data sets
- Technical environment for data processing, machine learning and delivery
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