6 machine learning misunderstandings

Ryan Francis for NetworkWorld:  Machine learning isn’t confined to science fiction movie plots anymore; it’s fueled the proliferation of technologies that touch our everyday lives, including voice recognition with Siri or Alexa, Facebook auto-tagging photos and recommendations from Amazon and Spotify. And many enterprises are eager to leverage machine learning algorithms to increase the efficiency of their network. In fact, some are already using it to enhance their threat detection and optimize wide area networks.

As with any technology, machine learning could wreak havoc on a network if improperly implemented. Before embracing this technology, enterprises should be aware of the ways machine learning can fall flat to avoid setting back their operations and turning the c-suite away from implementing this technology. Roman Sinayev, security intelligence software engineer at Juniper Networks, cites ways to avoid the top machine learning missteps.  Cont'd...

Comments (0)

This post does not have any comments. Be the first to leave a comment below.


Post A Comment

You must be logged in before you can post a comment. Login now.

Featured Product

Datanomix Production Monitoring

Datanomix Production Monitoring

Datanomix Production Monitoring delivers instant visibility into your shop floor performance. Through real-time alerts, simple machine connectivity, and our kick-ass coaching, you'll catch inefficiencies early, align your team with meaningful metrics, and respond faster to issues before they escalate. The software adapts without operator input and works out of the box with purpose-built Tracks (Efficiency, Delivery, Tooling, and more). Production Monitoring arms you with the data to make more, waste less, and lead with confidence. And while real-time visibility keeps you sharp in the moment, historical insights ensure you're learning from the past to drive ongoing continuous improvement.