After my article, “Role of Project Manager in Data Science”, a couple of program managers suggested me to elaborate the use case on meeting release commitments. We are going to explore simulation, one of the amazing concepts in Artificial Intelligence. Quantitative analytic techniques, such as the Monte Carlo simulation, helps program managers in decision making through probabilistic distributions of potential outcomes.

Monte Carlo relies heavily on the randomness of key variables in solving the problem. Along with key parameters, we also need to understand the relationship between them and sufficient data to analyze further. The five steps listed in “Forecasting the future: Let’s rewind to the basics” are essential to building an accurate model.

Source de l’article sur DZONE (AI)

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