Machine Learning

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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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Review: Keras sails through deep learning

Keras sequential models make deep neural network modeling about as simple as it can be

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LinkedIn open-sources a tool to run TensorFlow on Hadoop

The Tony project uses Hadoop's native scheduler to run TensorFlow jobs, making fault tolerance and GPU usage easier

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TensorFlow.js puts machine learning in the browser

The WebGL-accelerated library works with the Node.js server-side JavaScript runtime, but isn’t on par with Tensorflow’s Python API

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10 machine learning APIs developers will love

Tap the readymade machine learning models behind these cloud-based APIs to add a stroke of genius to your app

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How artificial intelligence is reshaping the insurance industry

Artificial intelligence is changing the world of insurance, improving underwriting and accessibility while making it more affordable for consumers. In the future, it may be able to make insurance obsolete

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Interview: Matei Zaharia on Spark and machine learning

Zaharia expounds on the reasons Spark has become the big data framework of choice and why he thinks his company’s melding of Spark and machine learning delivers unique value

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Machine learning: When to use each method and technique

What exactly can you do with machine learning? We explain the various methods and techniques available to you

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Kubeflow brings Kubernetes to machine learning workloads

Project works with TensorFlow library, eases ML deployments

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Why gaming AI won’t help make AI work in the real world—but could

The underlying game-theory principles could be applied to the real world, only if the test cases reflected the real world, not artificial fantasy environments

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What is CUDA? Parallel programming for GPUs

You can accelerate deep learning and other compute-intensive apps by taking advantage of CUDA and the parallel processing power of GPUs

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When data becomes a service

The need for data to fuel effective artificial intelligence solutions and how to collect it via model-as-a service and insights-as-a service

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What’s new in TensorFlow machine learning

Google’s TensorFlow 2.0 beta is expected later this year, with a focus on improving performance and correcting mistakes in compatibility and continuity

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