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.

What is Kotlin? The Java alternative explained

What is Jenkins? The CI server explained

What is Jenkins? The CI server explained

Jenkins offers a simple way to set up a continuous integration and continuous delivery environment for almost any combination of languages and source code repositories

What is Deno? A ‘better’ Node.js

What is Deno? A ‘better’ Node.js

From the creator of Node.js, Deno is a secure runtime for JavaScript and TypeScript that addresses Node’s shortcomings

InfoWorld’s 2020 Technology of the Year Award winners

InfoWorld’s 2020 Technology of the Year Award winners

InfoWorld recognizes the year’s best products in software development, cloud computing, data analytics, and machine learning

Deep learning vs. machine learning: Understand the differences

Deep learning vs. machine learning: Understand the differences

Both machine learning and deep learning discover patterns in data, but they involve dramatically different techniques

How to choose the right database for your application

How to choose the right database for your application

From performance to programmability, the right database makes all the difference. Here are 12 key questions to guide your selection

What is SQL? The first language of data analysis

What is SQL? The first language of data analysis

SQL is neither the fastest nor the most elegant way to talk to databases, but it is the best way we have. Here’s why

The best open source software of 2019

The best open source software of 2019

InfoWorld recognizes the leading open source projects for software development, cloud computing, data analytics, and machine learning

Semi-supervised learning explained

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

Automated machine learning or AutoML explained

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

Unsupervised learning explained

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

Supervised learning explained

Supervised learning explained

Supervised learning turns labeled training data into a tuned predictive model

Load More