While machine learning models are powerful tools, predicting the success of women-led startups comes with challenges. These models may struggle to account for the nuanced barriers that women entrepreneurs face, such as unequal access to funding and networks or gender biases in the business ecosystem. Ensuring that models are trained on balanced and comprehensive data is crucial to mitigate these limitations and improve prediction accuracy.
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