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Causal Thinking in the Age of Big Data: Modern Econometrics for Data Scientists

Causal Thinking in the Age of Big Data: Modern Econometrics for Data Scientists

Published 3 months ago
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This story was originally published on HackerNoon at: https://hackernoon.com/causal-thinking-in-the-age-of-big-data-modern-econometrics-for-data-scientists.
Predictive models now rule over modern analytics stacks from recommendation engines to demand forecasting and fraud detection.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-science, #analytics, #economics, #predictive-models, #modern-econometrics, #data-scientists, #machine-learning, #counterfactual-thinking, and more.

This story was written by: @dharmateja. Learn more about this writer by checking @dharmateja's about page, and for more stories, please visit hackernoon.com.

Predictive models now rule over modern analytics stacks from recommendation engines to demand forecasting and fraud detection. But as data scientists increasingly impact policy and strategy, the inherent limitation of prediction-only thinking has become obvious.

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