Personalized Product Recommendations

The aim is to enhance user experience by implementing a personalized product ranking system.
Your task is to develop an algorithm or model that can generate accurate and relevant product
rankings for individual users. The ranking system should consider factors such as user
preferences, past interactions, product popularity, and user similarity. It should be able to predict
the most suitable products for a user based on their unique characteristics and preferences.
You are not provided with a specific dataset for this challenge. Instead, you are expected to
design and implement a solution that simulates user interactions and generates personalized
rankings. You can define user profiles, product categories, and interaction patterns within your
solution.
To evaluate the effectiveness of your solution, you should define appropriate metrics for
measuring the accuracy and relevance of the rankings. You should also provide a report
explaining your approach, describing the algorithms or techniques used, and discussing the
strengths and limitations of your solution.