Challenge_Round_4
Challenge description:
You work as a data scientist at Amazon, one of the world's largest online retailers. To drive more sales and deliver valuable suggestions to customers, your manager has tasked you with building a product recommendation engine. Based on the product ratings given by customers, recommend 5 other products for each product in the given set of products. You are free to choose the approach that you see fits best. Clearly, in the interest of the company's sales, your recommendations should be meaningful to customers.
Additionally, your manager requires you to present the obtained recommendations in an interactive dashboard, and provide an explanation of your approach in an annotation (max. 200 words).
Note: Considering the dataset size, the recommendation engine can be computationally expensive to run. Feel free to use a small sample of the dataset, if computational resources are limited.
Key requirement: you must provide an explanation of your approach where you also clarify why you think your recommendation engine is good and would benefit the company and the customers.
Outcome:
An item-item recommender system and an interactive dashboard to present the recommendations.
Deliver your solution as a separate workflow and name it: Solution_Round_4_
Teams are strongly encouraged to submit high-quality work in order to improve their chances of getting maximum points. Don't be afraid to go the extra mile! :)
Dataset:
Provided in challenge folder.
Deadline:
April 7, 2024 (submission by 11:59 PM CET) **. Check the calendar of the tournament: https://info.knime.com/game-of-nodes
** We will verify the date and time of the latest edits.
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