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ML implementation for analyzing and estimating product prices / ML implementation för analys och estimation av produktpriser

Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. This project aims to use machine learning to assist in the pricing of products by estimating the prices to be inserted. Multiple machine learning models have been tested, and an artificial neural network has been implemented for estimating prices effectively. Through additional experimentation, the design of the network was fine-tuned to make it compatible with the project’s needs. The libraries used for implementing and managing the machine learning models are mainly ScikitLearn and TensorFlow. As a result, the trained model has been saved into a file and integrated with an API for accessibility.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kau-97981
Date January 2024
CreatorsKenea, Abel Getachew, Fagerslett, Gabriel
PublisherKarlstads universitet, Institutionen för matematik och datavetenskap (from 2013)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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