In Part I, I outlined an example of ML based product, as well as the differences between BI, DS & ML. In this post I will explain the steps a data scientist may take to building an ML based product…...

Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt ... (more…)

Graphcore, a $2.8B AI startup, looks like a failure! Their hardware and software simply don't measure up. They are require twice as much 7nm silicon to achieve slower results with worse pricing, TCO, and software support. (more…)

A speaker at a lecture that I have attended recently summarized the philosophy of machine learning this way: “All knowledge comes from observed data, some from direct sensory experience and some from indirect experience, transmitted to us either culturall... (more…)

Feature Engineering is paramount in building a good predictive model. It’s significant to obtain a deep understanding of the data that is being used for analysis. The characteristics of the selected features are definitive of a good training model. Why is... (more…)