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Polam, Mysura Reddy (2022) Sales and Logistics Analysis in E-Commerce using Machine Learning Models:UK. Masters thesis, Dublin, National College of Ireland.
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Abstract
Machine learning Technology is perhaps the most advanced use of AI technology that can produce results and train entirely on its own without being supervised learning in this research. The profitability of an e-commerce business is obtained and comprehended it using a machine learning model. This study made the best use of open-source technologies such as SQL, Powerbi, and Python, by employing machine learning approaches for business data regression models analyzed. Gradient boosting and Bagging regression yielded results with a 94% accuracy and just minor errors. In forecasting the company's sales and logistical success the scope and diversity of business patterns are also recognized at distinct periods and regional zones, allowing business owners to make intelligent choices. Furthermore, previous relevant work findings and research requirements are discussed to fill gaps in research feature adjustments and models are now being developed.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Mulwa, Catherine UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HD Industries. Land use. Labor > Business Logistics H Social Sciences > HF Commerce > Electronic Commerce Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Tamara Malone |
| Date Deposited: | 23 May 2023 16:44 |
| Last Modified: | 23 May 2023 16:44 |
| URI: | https://norma.ncirl.ie/id/eprint/6634 |
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