The development team will collect data on user behavior, including user search queries, purchasing history, and browsing behavior. The data will be preprocessed to remove noise and outliers, and transformed into a format that can be used by machine learning algorithms.
2. Feature Engineering:
The platform will be extensively tested and evaluated to ensure that the personalized recommendations are accurate and relevant to the user’s interests.
The team will perform feature engineering to extract relevant features from the data, such as user preferences, item popularity, and item similarity.
The platform will be extensively tested and evaluated to ensure that the personalized recommendations are accurate and relevant to the user’s interests.
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