Plug-and-play differential privacy for your tensorflow code
#GoogleAI has just released a new library for training machine learning models with (differential) privacy for training data.
where you would write tf.train.GradientDescentOptimizer
instead just swap in the DPGradientDescentOptimizer
Tutorial: https://github.com/tensorflow/privacy/blob/master/tutorials/mnist_dpsgd_tutorial.py
Link: https://github.com/tensorflow/privacy
#Privacy #tensorflow
🔗 tensorflow/privacy
Library for training machine learning models with privacy for training data - tensorflow/privacy
#GoogleAI has just released a new library for training machine learning models with (differential) privacy for training data.
where you would write tf.train.GradientDescentOptimizer
instead just swap in the DPGradientDescentOptimizer
Tutorial: https://github.com/tensorflow/privacy/blob/master/tutorials/mnist_dpsgd_tutorial.py
Link: https://github.com/tensorflow/privacy
#Privacy #tensorflow
🔗 tensorflow/privacy
Library for training machine learning models with privacy for training data - tensorflow/privacy
GitHub
privacy/tutorials/mnist_dpsgd_tutorial.py at master · tensorflow/privacy
Library for training machine learning models with privacy for training data - tensorflow/privacy
Massively Multilingual NMT in the wild: 100+ languages, 1B+ parameters, trained using 25B+ examples. Check out our new paper for an in depth analysis:
https://arxiv.org/abs/1907.05019
#GoogleAI
https://arxiv.org/abs/1907.05019
#GoogleAI
arXiv.org
Massively Multilingual Neural Machine Translation in the Wild:...
We introduce our efforts towards building a universal neural machine translation (NMT) system capable of translating between any language pair. We set a milestone towards this goal by building a...