Machine Learning

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Visual Studio Code’s Python add-on tries out data science

Data exploration and machine learning models are enabled via a Python language extension

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Review: MXNet deep learning shines with Gluon

With the addition of the high-level Gluon API, Apache MXNet rivals TensorFlow and PyTorch for developing deep learning models

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How to use Knime for data science

Free, open-source Knime allows you to visually assemble data processing “nodes” into machine learning, deep learning, and other analytics workflows

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Microsoft revamps machine learning tools for Apache Spark

The new open source release integrates Spark with Cognitive Toolkit and other Microsoft machine learning offerings

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Explainable AI: Peering inside the deep learning black box

Why we must closely examine how deep neural networks make decisions, and how deep neural networks can help

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How the Turing GPU will revolutionize immersive AI

AI, machine learning, and image manipulation have a lot in common, so it’s no surprise that GPUs can do both, which will bring us amazingly immersive apps

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7 cloud services to ease machine learning

Build, train, tune, and deploy machine learning and deep learning models in these end-to-end machine learning clouds

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6 ways to make machine learning fail

When learning, machine learning will make mistakes. Adopters need to anticipate that—and be careful not to make matters worse through human mistakes by IT and business

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Microsoft open-sources Infer.Net machine learning

The technology will become part of the ML.Net framework for statistical modeling and online learning

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Microsoft smartens up the ML.Net machine learning API

Microsoft’s TensorFlow-compatible machine learning framework debuts a reworked API for more flexible pipelines and improved prediction performance

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The future is cloudy, with a chance of success

True cloud computing metaphors: not every cloud is a rain cloud, and too much rain is disastrous for the unprepared

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Could gamification get workers to actually use AI?

Artificial intelligence has become more common in our personal lives, but what about in the workplace?

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Machine learning: How to go from theory to reality

A lack of skilled people continues to stymie the AI revolution. That’s why smart companies invest as much in cultural change as technology adoption—and Google shows how

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PyTorch 1.0 accelerates Python machine learning with native code

The PyTorch 1.0 release candidate introduces Torch Script, a Python subset that can be JIT-compiled into C++ or other high-speed code

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The best open source software for machine learning

InfoWorld’s 2018 Best of Open Source Software Award winners in machine learning and deep learning

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Bossies 2018: The Best of Open Source Software Awards

InfoWorld recognizes the leading open source projects for software development, cloud computing, big data, and machine learning

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How to use Azure ML in Windows 10

With local machine learning support, there’s no need to worry about shipping data to cloud services, especially where bandwidth or data protection can be an issue

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Azure’s new machine learning features embrace Python

New tools for Azure ML include integration with Python environments and self-tuning training for machine learning models

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How to solve AI’s reproducibility crisis

Society will never fully trust artificial intelligence’s actions unless they can be shown to produce reasonably repeatable results in line with what their developers claim

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Microsoft’s ML.Net framework adds TensorFlow scoring

This capability enables use of an existing model from Google’s TensorFlow deep learning and machine learning toolkit

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