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.
The best distributed NoSQL databases
Highly flexible and hugely scalable, NoSQL databases offer a range of data models and consistency options to suit your application
The best distributed relational databases
These SQL relational databases offer both horizontal scalability and support for ACID transactions—some on a global scale
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
Supervised learning explained
Supervised learning turns labeled training data into a tuned predictive model
10 new tricks your old database can do
You might be surprised by the powerful “NoSQL” features lurking in your old Oracle, SQL Server, MySQL, or PostgreSQL database
Reinforcement learning explained
Reinforcement learning uses rewards and penalties to teach computers how to play games and robots how to perform tasks independently
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
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