Abstract
Abstract: This project presents the development of a Laptop Recommendation System leveraging machine learning to assist users in selecting the most suitable laptop based on their specific requirements. By employing a content-based filtering algorithm, the system analyzes various attributes of laptops such as performance, price, and features to generate personalized recommendations. The machine learning model is trained on a comprehensive dataset of laptops, enabling it to accurately match user preferences with the optimal laptop options. The frontend of the system is developed using Vue.js, providing a dynamic and responsive user interface that enhances the overall user experience. This approach not only simplifies the decision-making process but also enhances user satisfaction by ensuring that the recommended laptops meet the individual needs of each user. The implementation of this system demonstrates the potential of machine learning, content-based filtering, and modern web development frameworks like Vue.js in creating intelligent, user-centric recommendation solutions
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