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Venture Capital Investing Process Improvement Through "Machine Learning"

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Mark Melin
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Technology executive Veronica Wu looks at machine learning and the process of Silicon Valley venture capital investing, a traditionally a “long shot” method, with an eye to improving win percentage. In a McKinsey question and answer session as part of their June quarterly report, Wu reveals how they use technology to build better predictive models for venture capital investing that integrate with humans. Like much of the gloss coming out of Silicon Valley regarding “machine learning,” however, the questions were light in key areas. This includes pointing to exactly where a machine scans information it wasn’t programmed to scan, “learn” knowledge or gain insight based on entirely new patterns not related to an if-then formula, and then...

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Mark Melin is an alternative investment practitioner whose specialty is recognizing the impact of beta market environment on a technical trading strategy. A portfolio and industry consultant, wrote or edited three books including High Performance Managed Futures (Wiley 2010) and The Chicago Board of Trade’s Handbook of Futures and Options (McGraw-Hill 2008) and taught a course at Northwestern University's executive education program.