Text analytics, sometimes called text data mining, is the process of uncovering insightful and actionable information, trends, or patterns from text. The extracted and structured data is much more convenient than the original text, making it easier to determine the information’s data quality and usefulness. Developers and data scientists can then use the mined data in downstream data visualizations, analytics, machine learning, and applications.

Text analytics aims to identify facts, relationships, sentiments, or other contextual information. The types of information extracted often start with tagging entities such as people’s names, places, and products. It can advance to assigning topics, determining

Disclaimer: nothing in this article should be constituted as mental health advice. This is anecdotal evidence from a technology journalist.

I’ve been a gamer since the early 1980s. I cut my teeth on Tempest and Donkey Kong in the local arcade. Gaming is my solace.

When big things happen in my life or in the world, and I need to wrap my head around them, my go-to coping mechanism is to play a game until I can think clearly and focus. This is how I’ve always blown off mental steam (for lack of a better way to put it).

But

Microsoft’s Azure Quantum, a public cloud ecosystem for building quantum computing applications, is now available for use in a public preview phase.

Launched February 1, the Azure Quantum cloud service is available for a free trial. Developers, integrators, researchers, and others can use the platform to build solutions leveraging Microsoft and partner tools in a trusted public cloud. Users can access a network of quantum researchers and developers, a resource library, and self-service or tailored development programs.

A key component of the platform is Microsoft’s open source Quantum Development Kit with the Q# language for quantum programming. Microsoft’s