Back in 2015, the TensorFlow machine learning framework was open-sourced by Google. And in no time, it turned out to be the well-liked platforms of its type. Nevertheless, businesses that wished to employ it have either do it themselves or have to unite with third parties. Google, to assist these firms, as well as bag some of this productive market itself, is introducing TensorFlow Enterprise that comprises practical, enterprise-grade backing, and advanced managed services on its Cloud.
Among TensorFlow Enterprise’s most significant features are that it will provide long-term backing. The search giant, for the framework’s some variants, will provide patches for 3 Years. Also, the company, for what seems to be an extra charge, will provide engineering support to a firm that are developing AI models from its TensorFlow and Google Cloud teams.
Every part of this, certainly, is intensely incorporated with the cloud services of Google. The company stated, “As TensorFlow was developed and open-sourced by Google, Google Cloud is exclusively placed to provide insights and support directly from the team of TensorFlow itself. Merged with our deep expertise in machine learning and AI, this makes TensorFlow Enterprise the finest means to operate TensorFlow.” Deep Learning Containers and Deep Learning VMs are also included by Google to make embarking with TensorFlow simpler and the firm has enhanced the enterprise variant for Google’s own Cloud TPUs and Nvidia GPUs.
Likewise, an online platform, TensorBoard.dev, was introduced by Google where machine learning experiments can be shared by researchers, data scientists, software developers, and machine learning practitioners as well as come together on machine learning projects. TensorBoard.dev, in a beta release stage at present, enables users to share with any person by uploading the machine learning experiments. It allows users to monitor model training metrics like loss & accuracy, picture the model graph, and see histograms of biases, weights, and other tensors.
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