Category Archives: Machine Learning

Decisioning Challenges of Driverless Cars

It is a lot harder to make an autonomous car than to sell the idea to AI-obsessed audiences. Christian Wolmar, the British author and broadcaster, said in this interview: “This is a fantasy that has not been thought through, and … Continue reading

Posted in Artificial Intelligence, Decision Modeling, Human-Machine Interaction, Machine Learning, Trends | 1 Comment

The end of the beginning

Benedict Evans, a partner at Andreessen Horowitz, gave a big annual  presentation on the state of tech – ‘the end of the beginning’ at a16z’s annual tech conference on Nov. 16, 2018. “Close to three quarters of all the adults on earth now have … Continue reading

Posted in Digital Transformation, Human-Machine Interaction, Innovation, Machine Learning, Trends | Leave a comment

The Myth of Data-Driven Natural Language Understanding

Walid Saba published a short presentation on the difference between Natural Language Processing (NLP) and Natural Language Understanding (NLU) and why the data-driven approach, while useful for some NLP tasks, is irrelevant to NLU. Link

Posted in Artificial Intelligence, Machine Learning, Natural Language Processing | Leave a comment

Google’s What-If Tool for Machine Learning Models

Building effective machine learning (ML) systems means asking a lot of questions. It’s not enough to train a model and walk away. Instead, good practitioners act as detectives, probing to understand their model better: How would changes to a datapoint affect … Continue reading

Posted in Explanations, Machine Learning | Leave a comment

How DMN could help to explain ML outcome

Dr Jan Purchase just published an article “Better AI Transparency Using Decision Modeling“, in which he describes several possible ways to provide reasonable explanations to the outcome of machine learning algorithms. Jan without hesitations describes practical limitations of the described approaches.  Jan … Continue reading

Posted in Decision Modeling, DMN, Machine Learning | Leave a comment

Chaining Machine Learning and Optimization Models

Machine learning is about predicting, while optimization is about solving (searching for the values of variables that lead to the best outcomes). The latest Nathan Brixius’s post discusses different ways of combining optimization and machine learning: 1. Optimization as a means … Continue reading

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How to use traditional scorecards and AI together

Which works better for modeling credit risk: traditional scorecards or artificial intelligence and machine learning? Given the excitement around AI today, this question is inevitable. The fact is that traditional scorecard methods and AI bring different advantages to credit risk … Continue reading

Posted in Business Analytics, Decision Modeling, Machine Learning | Leave a comment