Martin Heller
Contributing Editor
Martin Heller is a contributing editor and reviewer for InfoWorld. Formerly a web and Windows programming consultant, he developed databases, software, and websites from his office in Andover, Massachusetts, from 1986 to 2010. More recently, he has served as VP of technology and education at Alpha Software and chairman and CEO at Tubifi. Disclosure: He also writes for Hewlett-Packard's TechBeacon marketing website.
Natural language processing explained
Deep learning has improved machine translation and other NLP tasks by leaps and bounds
Deep learning explained
Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data
Machine learning explained
Able to learn from data, machine learning algorithms can solve problems that are too complex to solve with conventional programming
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
Machine learning algorithms explained
Machine learning uses algorithms to turn a data set into a model. Which algorithm works best depends on the problem
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
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
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
