What’s new in TensorFlow machine learning | Tech News
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TensorFlow, Google’s contribution to the world of machine learning and data science, is a general framework for quickly developing neural networks. Despite being relatively new, TensorFlow has already found wide adoption as a common platform for deep learning, due to its powerful abstractions and ease of use.
Where to download TensorFlow
Installation instructions for TensorFlow on Ubuntu Linux, MacOS, and Microsoft Windows are available on the TensorFlow project page. Docker users can grab a pre-built TensorFlow Docker image directly from Docker Hub. You can also compile the sources into a binary; the sources are available on GitHub.
Current version: TensorFlow 1.8 new features
New additions in TensorFlow 1.8 include:
- The ability to prefetch data to GPU memory. This can speed up GPU operations where the data is known ahead of time, since it can then be copied to the GPU all at once.
- Support for third-generation pipeline config for Cloud TPUs, “which improves performance and usability,” Google says. TPUs are hardware units available exclusively in Google Cloud that accelerate TensorFlow performance.
- Contributed support for reading and writing protocol buffers from within Tensorflow, as well as support for older RPC communication, by way of the
tf.contrib.protoandtf.contrib.rpclibraries.
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