From the course: Building Recommender Systems with Machine Learning and AI

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The cold start problem (and solutions)

The cold start problem (and solutions) - Python Tutorial

From the course: Building Recommender Systems with Machine Learning and AI

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The cold start problem (and solutions)

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- [Instructor] One of the better known issues with recommender systems is what is known as the cold-start problem. If a brand new user arrives at your site, what do you recommend to them when you know nothing about them yet? And new users aren't the only problem. What about new items in your catalog? How do they get recommended when there is no data on them yet to pair them with other items? When faced with a new user, your options are limited. The one saving grace is that a new user isn't new for long. Assuming they stay in your site at all, you'll soon have some information to work with that indicates their interests. As soon as this new user looks at a new item, you'll have at least some implicit information about this user's interests, even if it's just that this user looked at this product. If you're lucky, they landed on your site on an actual product page, and you can just recommend other items similar to the item they are looking at. As it turns out, the thing a person is…

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