If you’re doing work in statistics, data science, or machine learning, the odds are high you’re using Python. And for good reason, too: The rich ecosystem of libraries and tooling, and the convenience ...

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One of the big surprises of the past few years has been the spectacular rise in the use of Python* in high-performance computing applications. With the latest releases of Intel® Distribution for ...

The MKL libraries for accelerating math operations debuted in Intel's own Python distribution, but now other Pythons are following suit Last year Intel became a Python distributor, offering its own ...

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Snowflake and Anaconda recently announced the general availability of Snowpark for Python, a solution that embeds Anaconda’s data and machine learning packages within Snowflake’s Data Cloud.

Over the past year I’ve reviewed half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and ...

With the current data science boom, many companies and organizations are stepping outside of their traditional business models to scope work that applies rigorous quantitative methodology and machine ...