Google updates TensorFlow to enable open source distributed machine learning models

Google has updated its TensorFlow open source machine learning code to enable it to be deployed on cloud platforms and across hundreds of distributed machines. TensorFlow 0.8 now gives developers the option to build machine learning models that can run operations on distributed clusters of computers. Machine learning software gets smarter the more data it ingests and analyses, so deploying TensorFlow across operations running on multiple machines gives the framework far greater scope to learn at scale. This ability to scale across distributed machines allows TensorFlow models to be trained and deployed on the Google Cloud Platform, and complements Google Cloud Machine Learning, a new smart service offered to companies and developers looking to build Google cloud-based machine learning software and apps. Equally, having access to the combined power of…


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