Reviews
The best machine learning and deep learning libraries
TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models
TensorFlow 2 review: Easier machine learning
Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment
Amazon Neptune review: A scalable graph database for OLTP
Amazon’s graph database service offers ACID properties, immediate consistency, and auto-scaling storage for billions of relationships
Review: UiPath aces robotic process automation
UiPath Enterprise RPA Platform is a remarkably complete toolkit for process automation that is also remarkably easy to use
Review: Kinetica analyzes billions of rows in real time
GPU database is not only hugely scalable, but integrates graph analysis, location intelligence, and machine learning with standard SQL
AnzoGraph: A graph database for deep analytics
AnzoGraph is a fast, horizontally scalable, OLAP graph database that brings a wealth of analytics capabilities to large graphs
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
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
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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