Author Archives: Thomas W. Dinsmore

Notes on the Forrester “Wave”

Forrester recently published the Wave™ for Predictive Analytics And Machine Learning Solutions. You can purchase a copy from Forrester for $2,495, or get a free copy here. When Forrester last delivered this analysis in 2015, they called it the Wave™ for Big Data Predictive Analytics Solutions. So, I guess that Big Data is “out” and machine learning is “in.” The chart below shows the

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IBM Launches “IBM Machine Learning”

It’s only March, but already IBM leads the software industry in gasbaggery. Gartner’s most recent Magic Quadrant for Data Science Platforms includes this little gem: Customers are often confused by mismatches between (IBM’s) marketing messages and actual, purchasable products. That’s a polite way to say that IBM marketing messages have enough hot air to float a fleet of balloons over the Bernese

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A Note to Readers

As we welcome the New Year — belatedly — I want to extend many thanks to those who read the scribblings on this blog. I’m particularly grateful for the great response to my recent four-part review of the year in machine learning and deep learning. Looking out over the next several months, some exciting long-form stories are coming: the SQL-in-Hadoop

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The Year in Machine Learning (Part Four)

This is the fourth installment in a four-part review of 2016 in machine learning and deep learning. — Part One covered Top Trends in the field, including concerns about bias, interpretability, deep learning’s explosive growth, the democratization of supercomputing, and the emergence of cloud machine learning platforms. — Part Two surveyed significant developments in Open Source machine learning projects, such as R, Python, Spark, Flink,

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