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Review: OmniSci GPU database lifts huge data sets

GPU acceleration of database, rendering, and visualization enables interactive exploration of data sets with billions of rows


Das Keyboard 5Q lights up for developers

High-end keyboard is designed to keep developers and IT pros in the loop with key LEDs that double as notifications

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The best machine learning and deep learning libraries

Why TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models

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Review: Google Cloud AutoML is truly automated machine learning

Google’s AutoML lets you create customized deep learning models without any knowledge of data science or programming

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Cloud IDE review: AWS Cloud9 vs. Eclipse Che vs. Eclipse Theia

You don’t have to develop locally to get full IDE support. We compare three great tools that let you edit and debug code from a browser

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Review: Azure Machine Learning challenges Amazon SageMaker

Microsoft Azure’s plush, Python-based environment covers the full machine learning and deep learning development cycle

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Review: The 6 best JavaScript IDEs

WebStorm, Visual Studio 2017, Visual Studio Code, NetBeans, Komodo, and Eclipse pull out the stops for JavaScript, Node.js, and friends

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Review: The 10 best JavaScript editors

Sublime Text, Visual Studio Code, Brackets, and Atom rise to the top, but several others are also worth considering


TigerGraph review: A graph database designed for deep analytics

Highly parallelized and horizontally scalable, TigerGraph shines for use cases that require multi-hop analytic queries

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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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