From the course: Machine Learning in Mobile Applications

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ML frameworks

ML frameworks

From the course: Machine Learning in Mobile Applications

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ML frameworks

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The landscape of machine learning is still highly fragmented, with several model formats and competing standards. Here are some of the common frameworks you may encounter, but there are many others. TensorFlow is backed by Google and focuses on deep learning. It has widespread popularity in the business community. Scikit-learn is also an open-source framework started by Google Summer of Code project. Caffe is a Berkeley AI research project that is now open source. Caffe spawned Caffe2, a deep learning framework which is backed by Facebook. ML.NET is a Microsoft machine learning framework using common .NET languages. Microsoft Cognitive Toolkit is another Microsoft library that focuses on machine learning. While there are many competing model standards, luckily many products can work with or import other standards. The common feature among all of these offerings is that they are geared towards data scientists, not your average developer. When looking at implementing server-side machine…

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