Access and Feeds

Open Source Machine Learning: Open Source Dominates Preferred ML and AI Tools and Frameworks

By Dick Weisinger

Machine Learning (ML) and Artificial Intelligence (AI) technologies are being developed and adopted at a rapid pace. This area has become a hot topic in 2017. Interestingly, many of the more prominent tools are Open Source. The technologies are being used with a wide variety of applications, like search, data mining, spam detection, character recognition, autonomous vehicles, online recommendations

Many of those Open Source tools offer a Python interface to allow developers to jump in quickly. For example, there are core libraries like NumPy, SciPy and SciKit. Keras is a Deep Learning library and TensorFlow is Google’s Open Source Machine Learning tool.

Doug Dineley, executive editor of InfoWorld, said that “if you’re looking for something to blame for the blistering pace of change in information technology, look no further than open source. Open source is reinventing how we develop software, analyze data, and build scalable systems right before our eyes.”

Al Gillen, Vice President at IDC, said that “Open Source software has been making waves across the industry, and here in the cognitive/AI software market, specifically in the more focused machine learning/deep learning segment, the majority of the offerings vying for position are based on or are open source software, a likely sign of things to come.”

Digg This
Reddit This
Stumble Now!
Buzz This
Vote on DZone
Share on Facebook
Bookmark this on Delicious
Kick It on DotNetKicks.com
Shout it
Share on LinkedIn
Bookmark this on Technorati
Post on Twitter
Google Buzz (aka. Google Reader)
0 comments on “Open Source Machine Learning: Open Source Dominates Preferred ML and AI Tools and Frameworks
1 Pings/Trackbacks for "Open Source Machine Learning: Open Source Dominates Preferred ML and AI Tools and Frameworks"

Leave a Reply

Your email address will not be published. Required fields are marked *

*

eighteen − fourteen =