TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet are the seven most popular frameworks for developing AI applications. Artificial Intelligence (AI) is a rapidly ...
Over the past year I’ve reviewed half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and ...
Yahoo, model Apache Spark citizen and developer of CaffeOnSpark, which made it easier for developers building deep learning models in Caffe to scale with parallel processing, is open sourcing a new ...
Over at IBM, Sumit Gupta writes that the company has enabled record-breaking image recognition capabilities that make Deep Learning much more practical at scale. It currently may take days or even ...
Hardware support is now available for TensorFlow from NVIDIA and Movidius, intended to accelerate the use of deep neural networks for machine learning applications. Each framework has advantages and ...
A subcategory of machine learning, deep learning uses multi-layered neural networks to automate historically difficult machine tasks—such as image recognition, natural language processing (NLP), and ...
Like superheroes, deep learning packages usually have origin stories. Yangqing Jia created the Caffe project while earning his doctorate at U.C. Berkeley. The project continues as open source under ...
It's possible to create neural networks from raw code. But there are many code libraries you can use to speed up the process. These libraries include Microsoft CNTK, Google TensorFlow, Theano, PyTorch ...
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