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.

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

Deep learning frameworks: PyTorch vs. TensorFlow

Deep learning frameworks: PyTorch vs. TensorFlow

If you actually need a deep learning model, PyTorch and TensorFlow are both good choices

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

Couchbase review: A smart NoSQL database

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

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 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

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

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

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

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 explained

Supervised learning turns labeled training data into a tuned predictive model

10 new tricks your old database can do

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 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

Natural language processing explained

Deep learning has improved machine translation and other NLP tasks by leaps and bounds

What is deep learning? Algorithms that mimic the human brain

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

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 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 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

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: 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

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