Explorium's Data Insights Blog
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Interpretability and explainability (Part 2)
The whole idea behind interpretable and explainable ML is to avoid the black box effect.
Interpretability and explainability (Part 1)
The whole idea behind interpretable and explainable ML is to avoid the black box effect.
The ultimate machine learning model deployment checklist
While there is some room for error while integrating models into production environments, there is also a very good probability that these issues will eventually lead to disaster. And that’s exactly why we have created this pre-model deployment checklist.
Who’s the painter?
Better features, better data
The spectrum of complexity
Demystifying the old battle between transparent, explainable models and more accurate, complex models.
Why automating data science will kill the BI industry
Machine learning models are mathematical models that leverage historical data to uncover patterns which can help predict the future to a certain degree of accuracy. And when it comes to running a business, the ability to predict and make data-driven decisions (from the ability to identify customer churn before it happens, to optimizing promotions and […]