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 […]
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 […]
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 […]
Power BI: Creating and Sharing Power BI Templates
Templates are great for word processors and spreadsheets; they save time and enforce consistency. Templates are great for Power BI, too, but Power BI templates must solve a minor complication not faced by its sister Office applications. The measures, columns, and visualizations that collectively constitute a Power BI report are based on a specific data […]
New Improved SQL Server 2019! Now with more Spark!
If your server racks are anything like mine, they look impressive and powerful, clean and efficient. From the front, that is. Look behind the rack and there is a tangled rat’s nest of power cables, network connections, and those big clumsy things connecting to KVM switches. It’s worse on the inside. Data platforms and software […]