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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM17996

Smart Start-Up Analyzer: Prediction Model, Analysis tool for Venture Capitals using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM17996

Volume:

7 |

3 |

Mar 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MST

Mantej Singh Tuli

SG

Shreyas G

DAN

Dheemanth A N

SCR

Sree Chand R

AYK

Anupama Y K

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Abstract

Artificial intelligence (AI) has emerged as a powerful technology with the potential to revolutionize many different industries and fields. In recent years, AI has been applied in a variety of areas, comprising healthcare, finance, and even venture capital. Venture capital is a form of private equity that involves investing in startups and other early-stage companies with high growth potential. Venture capitalists often provide funding, expertise, and other resources to help these companies succeed and generate returns for investors. Our research suggests that AI has the potential to play an important role in the venture capital industry, helping venture capitalists make more informed and profitable investments. In the following sections of the paper, we will provide a more detailed background on the history and evolution of AI, and discuss the current state of the art in AI technology. We will then present a literature review of previous research on the use of AI in venture capital, and outline our research approach. Ultimately, we will bestow our findings and review their implications for the future of venture capital and AI.

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Cite This Article

Mantej Singh Tuli, Shreyas G, Dheemanth A N, Sree Chand R, Anupama Y K, "Smart Start-Up Analyzer: Prediction Model, Analysis tool for Venture Capitals using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 3, Mar 2023. https://doi.org/10.55041/IJSREM17996

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Publication Date

10/2/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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