Tag Archives: Microsoft

ML/AI Vendor Roundup: September 2018

Product enhancements, customer references, partnerships, acquisitions, or other significant contributions to machine learning. In general industry news, Forrester releases 2018 “Wave” reports for data science and machine learning. Positive implications for SAS, IBM, RapidMiner, Oracle, and Domino Data Labs. Negative implications for Microsoft, Dataiku, Anaconda, and Google Cloud Platform. Full story here. Vendors listed below in alphabetical order. Dataiku Dataiku

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Forrester’s 2018 PAML “Waves”

Forrester just published two “Wave” reports for predictive analytics and machine learning. The first, covering “multi-modal” solutions, is available here for free. A second report, covering notebook-based solutions, is available here (registration required.) Forrester plans to publish a third report, covering automated machine learning vendors, in 2019. Kudos to Forrester for understanding the diversity of the data science tools market.

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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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The Year in Machine Learning (Part Three)

This is the third installment in a four-part review of 2016 in machine learning and deep learning. In Part One, I 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. In Part Two, I surveyed significant developments in Open Source machine learning projects, such as R, Python,

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