Organize Your DAX Measures in Power BI

Like many others, I wrote my first DAX measures in Excel Power Pivot. It seemed so natural to add measures in the editing area associated with the fact table I never considered any other way. But while measures specify one or more tables in their code definition, there is really no restriction on “where” they […]
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Curing Python Envy with ML.Net

Curing Python Envy with ML.Net In early May 2019,  Microsoft released ML.Net 1.0, marking the graduation of ML.Net from research project to Release Candidate. In contrast with many machine learning platforms, which usually provide a Python API, ML.Net, as its name suggests, provides a direct interface for code targeting .Net core, whether written in C#, […]
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Parallel or Perish – An Overview

I’m pleased to begin the first of a series of blogs on parallel processing, a topic which is no longer optional in the world of machine learning and AI. In this introductory note, we’ll take an overview of the field which, for better or for worse, is becoming more complex every day. Today we are […]
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Beware the Local Minima

My career would probably be going better if I were not so easily distracted. A recent distraction occurred when I was browsing for some simple Keras code to test an installation of Intel’s PlaidML library. I came across a linear regression performed using Keras but the graph didn’t look quite right. There were more points […]
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Does Intel Python Deliver?

Intel’s distribution of Python, created in collaboration with Anaconda, is billed by the hardware giant as a distribution created for performance. Specifcally, the numerical performance demanded by scientific research and machine learning. Claims are bandied about referring to Python that executes at machine-language speeds, but does Intel Python really deliver? I won’t use the word […]
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