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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Using Postman to Learn the Azure Artificial Intelligence APIs

Azure Artificial Intelligence can be accessed by virtually any programming platform; all that is necessary is to formulate and send the appropriate http request and correctly parse the response. The Application Program Interface (API) is the same whether you prefer C#, Python, Node.js, or a host of other environments. But what if you are just […]
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Parallel or Perish: Distributed Multiprocessing with MPI and Python

In the previous installment, we discussed how distributed multiprocessing architectures come to dominate the supercomputing arena. Smaller, somewhat less than “super”, clusters continue to find practical applications. As we mentioned, Hadoop and Spark clusters are designed to map code to multiple computers so the code can be applied to a great deal of data distributed […]
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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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5 best practices to perform data wrangling with Python

Data wrangling is the process of cleaning and structuring complex data sets for easy analysis and making speedy decisions in less time. Due to the internet explosion and the huge trove of IoT devices there is a massive availability of data, at present. However, this data is most often in its raw form and includes a lot […]
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