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.
Visual Studio Code vs. Visual Studio: How to choose
Deciding between Visual Studio Code and Visual Studio may depend as much on your work style as on the language support and features you need. Here’s how to decide
Snowflake review: A data warehouse made better in the cloud
A fast, no-fuss data warehouse as a service, Snowflake scales dynamically to give you the performance you need exactly when you need it
Semi-supervised learning explained
Using a machine learning model’s own predictions on unlabeled data to add to the labeled data set sometimes improves accuracy, but not always
PyTorch vs. TensorFlow: How to choose
If you actually need a deep learning model, PyTorch and TensorFlow are the two leading options
Automated machine learning or AutoML explained
AutoML frameworks and services eliminate the need for skilled data scientists to build machine learning and deep learning models
Couchbase review: A smart NoSQL database
Flexible, distributed document database offers an easy query language, mobile synch, independently scalable services, and strong consistency within a cluster
The best NoSQL databases
Highly flexible and hugely scalable, NoSQL databases offer a range of data models and consistency options to suit your application
Unsupervised learning explained
Unsupervised learning is used mainly to discover patterns and detect outliers in data today, but could lead to general-purpose AI tomorrow
The best graph databases
These stellar databases combine horizontal scalability with highly efficient engines for storing and analyzing connected data
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
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
What is natural language processing? AI for speech and text
Deep learning has improved machine translation and other natural language processing tasks by leaps and bounds
What is deep learning? Algorithms that mimic the human brain
Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data
What is machine learning? Intelligence derived from data
Machine learning algorithms learn from data to 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
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