Machine Learning and Quantum Intelligence for Challenging Data Scenarios
The advent of more accessible Machine Learning (ML) methods has opened new avenues for ML-driven applications in traditionally data-scarce domains. One such challenging area that we explore in this presentation is predicting the success of start-ups where data scarcity and quality pose significant obstacles. In this paper, we propose leveraging Machine Learning and specifically Quantum Machine Learning, to address the complexities of decision-making. We argue that the unique features of the dataset can be effectively processed using Quantum Machine Learning (QML). This offers advantages in creating feature spaces not achievable through classical methods, thereby compensating for the limitations of the data. Moreover, the potential acceleration of processing capability with the advent of large-scale quantum processors adds another dimension to the advantages.
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