Project Description <<<<<<< HEAD

Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast of the Semantics, a large language ocean.

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The Predicting Startup Success project aims to leverage machine learning algorithms to predict the likelihood of success for currently operating startups. By utilizing a dataset of startup characteristics, including financial metrics, team relationships, milestones, and funding details, we built a machine learning model that provides insights into whether a startup is likely to succeed (defined as achieving an IPO or acquisition) or fail. Through the application of various algorithms, including Decision Trees, Random Forest, and Support Vector Machines, this model offers investors and stakeholders a valuable tool to make informed decisions, mitigate risks, and optimize their portfolios.

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Project Date <<<<<<< HEAD March 9th, 2020 ======= Aug 27th, 2023 >>>>>>> 81cda6ec38c75f8568fd199ea616687b577021d8

Role <<<<<<< HEAD Identity, Web Design ======= Developer, AI,ML >>>>>>> 81cda6ec38c75f8568fd199ea616687b577021d8

<<<<<<< HEAD Client unslate ======= Location SR university >>>>>>> 81cda6ec38c75f8568fd199ea616687b577021d8

Visit <<<<<<< HEAD https:/// ======= https://doi.org/10.1063/5.0217506 >>>>>>> 81cda6ec38c75f8568fd199ea616687b577021d8