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Abstract

With the rapid enhancement of modern technology, we are more engaged with online shopping due to its high comfort, ease to use, safety etc. So we find a problem for laptop product evaluation in the online as well as offline market. The demand for laptops were rapidly increased after the lockdown in India. In the June quarter of 2021, 4.1 million units were shipped and which is the highest shipment in five years. In laptops, the price is acquired from its RAM, ROM, CPU, GPU, Touch screen, model, trends etc. Sometimes it is very much difficult for the customer as well as the retailer to fix a price with the certain characteristics of laptops so that both can evaluate the price and be satisfied with it. So we are going to develop a model for predicting the laptop price as per its properties. Because of any casual customer, this model will help in selecting and deciding on a laptop whether to buy or not, and also will reduce the time and effort that anyone will have to spend manually researching the market price. This paper will focus on Human-centric computing applications for laptop price prediction because it can be analyzed by those well structured data that itself enhanced machine learning techniques, easily representable as a set of qualified parameters etc. So, we will develop an attribute-based prediction model for laptops using Regression machine learning algorithm.

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