Machine Learning Times
Machine Learning Times
How Machine Learning Works for Social Good
  Originally published in KDnuggets, Nov 2020. This article...
Diversity and Collaborative Problem Solving to Address Wicked Data Ethics Problems
 The complexity of the ethical issues facing professionals who...
Climate Tech Needs Machine Learning, Says PAW Climate Conference Chair
  Straight from the horse’s mouth – the founding...
Predictive Policing: Six Ethical Predicaments
  Originally published in KDNuggets. This article is based...

7 months ago
Overcoming the Explainability Challenges of Machine Learning Models

 Some History Machine Learning Models, which have historically been referred to as predictive models, are not new. Any early practitioner in this field would emphasize that the two key deliverables of any model are as follows: its benefits to the business or organization Model Explainability (i.e. what is inside the model) The model benefits are essentially about optimizing ROI where the challenge might be to identify those key metrics that impact ROI.  For a marketing campaign, the use of the model helps the marketer to better allocate his or her budget towards those individuals who are more likely

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