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