| dc.contributor.author | Raza, Abdullah Bin Reg # 59983 | |
| dc.contributor.author | Azfar, Manaal reg # 60029 | |
| dc.contributor.author | Shaikh, Azka Reg # 60036 | |
| dc.date.accessioned | 2026-07-02T04:51:51Z | |
| dc.date.available | 2026-07-02T04:51:51Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/21359 | |
| dc.description | Supervised by Fasiha Ikram | en_US |
| dc.description.abstract | The study, entitled "Online investment Assistant," is an application that aims to guide and lead the user to make the most appropriate possible investment decision. The purpose is not to have a computer surreptitiously anticipate the outcome of a stock, but to put computer processing capacity and artificial intelligence approaches to use in the e-commerce sector. The tool is designed to help investors make stock investments based on their budget. The online investment assistant allows the usei to keep track of the top trending products. It recommends the user the top trending products in the market and provides them with a list of manufacturers who manufacture those products. This will enable them to get their hands on them. Then, by selecting the manufacturer or vendor from which the user is purchasing the niche, our tool will present the market strategy for the selected niche. Our investment assistant targets employees who are micro investors, investing the average amount of their savings. As a first step, our app allows them to enter their investment amount, and then the activity cycle proceeds to the selection of a niche. Additionally, it displays the most trending and bestselling products among a range of categories, along with A.I.-driven modules of best sellers for them and for the best marketing strategy | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Bahria University Karachi Campus | en_US |
| dc.relation.ispartofseries | BSCS;MFN BSCS 440 | |
| dc.title | ONLINE INVESTMENT ASSISTANT | en_US |
| dc.type | Project Reports | en_US |