From the course: The Data Science Playbook for Private Equity and Venture Capital
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Utilizing supervised machine learning applications
From the course: The Data Science Playbook for Private Equity and Venture Capital
Utilizing supervised machine learning applications
- [Instructor] The core of the data science playbook for private equity and venture capital firms is at the operation stage. It's here that we see supervised machine learning having the most utilization. So what is supervised machine learning? Simply put, these are predictive models where there's an outcome. There's something specific that you have as a target variable, that you're trying to understand and predict. That target variable could be profitability, it could be efficiency, it could be risk, it could be a forecast. It could be attrition rates, it could be promotion rates. Regardless of the outcome of interest, the key to supervised machine learning is understanding that there is something you're trying to predict. The question then becomes, so what are these data science playbook elements? And how can they be applied across the entire portfolio? Let's start with some common elements of the data science…
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