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This project focuses on developing a laptop recommendation system utilizing a content-based approach. By employing cosine similarity, we analyze laptop features and specifications to determine similarities between different models. This allows us to provide personalized recommendations based on user preferences and requirements.

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Laptop-Recommendation-System

Our Laptop Recommendation System will recommend similar laptops to users based on their search results. This is Content Based Recommendation System which uses Cosine Similarity techninque to recommend similar Laptops

Dataset: Web Scraping from this Website https://www.smartprix.com/laptops/

Link for Video Demo: https://www.youtube.com/watch?v=1ZlExl-eeRA

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When a user searches for the Laptop (Auto Suggestion)

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Details of the Laptop which user searched for

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Recommended Laptops for the user based on Search Results

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Details of one of the Recommended Laptop:

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How Cosine Similarity Works?

Cosine Similarity is a measurement that quantifies the similarity between two or more vectors . The cosine similarity is the cosine of the angle between vectors. The vectors are typically non-zero and are within an inner product space.

The cosine similarity is described mathematically as the division between the dot product of vectors and the product of the euclidean norms or magnitude of each vector.

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This project focuses on developing a laptop recommendation system utilizing a content-based approach. By employing cosine similarity, we analyze laptop features and specifications to determine similarities between different models. This allows us to provide personalized recommendations based on user preferences and requirements.

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