APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNING PIPELINE
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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A retail company wants to start personalizing product recommendations to visitors of their website. They have2 historical data of what products the users have purchased and want to implement the system for new users, prior to them purchasing a product. What’s one way of phrasing a machine learning problem for this situation?
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Predict if a user will buy the product based on all the other products they bought
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Classify the products to categories to recommend the user based on the most common category bought
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Predict the next item that user will buy based on every the products all users bought
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Predict the item the user will buy based on other users’ purchase history and the product ratings and reviews
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Explanation:
Detailed explanation-1: -Amazon Personalize allows developers to quickly build and deploy curated recommendations and intelligent user segmentation at scale using machine learning (ML).
Detailed explanation-2: -The most important thing is to establish exactly how the products you’re recommending are relevant to your customer. On the homepage, that might mean you’re showing your “Best Selling Items”. On product pages, you can show products ‘Frequently bought together’ to encourage higher average cart values.
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