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 open source software of 2020
InfoWorld picks the year’s best open source software for software development, cloud computing, data analytics, and machine learning
10 MLops platforms to manage the machine learning lifecycle
Machine learning lifecycle management systems rank and track your experiments over time, and sometimes integrate with deployment and monitoring
What are deepfakes? AI that deceives
Deepfakes extend the idea of video compositing with deep learning to make someone appear to say or do something they didn’t really say or do
What is quantum computing? Solutions to impossible problems
Quantum computing has great promise to solve problems that are too hard for classical computers to solve in reasonable amounts of time, but they are not yet practical
Amazon Braket: Get started with quantum computing
Amazon’s quantum computing service is currently good for learning about quantum computing and developing NISQ-regime quantum algorithms, but stay tuned
What is face recognition? AI for Big Brother
Facial recognition is becoming more accurate, but some systems exhibit racial bias and some uses of the technology are controversial
How to use TensorFlow in your browser
Take advantage of TensorFlow.js to develop and train machine learning models in JavaScript and deploy them in a browser or on Node.js
What is computer vision? AI for images and video
Computer vision systems are not only good enough to be useful, but in some cases more accurate than human vision
How to choose a cloud machine learning platform
12 capabilities every cloud machine learning platform should provide to support the complete machine learning lifecycle
Deeplearning4j: Deep learning and ETL for the JVM
Aimed at integrating models with Java applications, Deeplearning4j offers a stack of components for building JVM-based applications that incorporate AI
Kaggle: Where data scientists learn and compete
By hosting datasets, notebooks, and competitions, Kaggle helps data scientists discover how to build better machine learning models
-
Case Study
Sponsored -
Video/Webcast
Sponsored -
Video/Webcast
Sponsored -
Analyst Report
Sponsored -
Video/Webcast
Sponsored
