forked from 626_privacy/tensorflow_privacy
98 lines
4.3 KiB
YAML
98 lines
4.3 KiB
YAML
# TODO(b/181782485): Switch to the main book for launch - /responsible_ai/_book.yaml
|
|
book_path: /responsible_ai/_book.yaml
|
|
project_path: /responsible_ai/_project.yaml
|
|
title: TensorFlow Privacy
|
|
description: >
|
|
Overview of TensorFlow Privacy library.
|
|
landing_page:
|
|
nav: left
|
|
custom_css_path: /site-assets/css/style.css
|
|
rows:
|
|
- heading: Privacy in Machine Learning
|
|
items:
|
|
- classname: devsite-landing-row-50
|
|
description: >
|
|
<p>
|
|
An important aspect of responsible AI usage is ensuring that ML models are prevented from
|
|
exposing potentially sensitive information, such as demographic information or other
|
|
attributes in the training dataset that could be used to identify people.
|
|
One way to achieve this is by using differentially private stochastic gradient descent
|
|
(DP-SGD), which is a modification to the standard stochastic gradient descent (SGD)
|
|
algorithm in machine learning.
|
|
</p>
|
|
<p>
|
|
Models trained with DP-SGD have measurable differential privacy (DP) improvements, which
|
|
helps mitigate the risk of exposing sensitive training data. Since the purpose of DP is
|
|
to help prevent individual data points from being identified, a model trained with DP
|
|
should not be affected by any single training example in its training data set. DP-SGD
|
|
techniques can also be used in federated learning to provide user-level differential privacy.
|
|
You can learn more about differentially private deep learning in
|
|
<a href="https://arxiv.org/pdf/1607.00133.pdf">the original paper</a>.
|
|
</p>
|
|
|
|
- code_block: |
|
|
<pre class = "prettyprint">
|
|
import tensorflow as tf
|
|
from tensorflow_privacy.privacy.optimizers import dp_optimizer_keras
|
|
|
|
# Select your differentially private optimizer
|
|
optimizer = tensorflow_privacy.DPKerasSGDOptimizer(
|
|
l2_norm_clip=l2_norm_clip,
|
|
noise_multiplier=noise_multiplier,
|
|
num_microbatches=num_microbatches,
|
|
learning_rate=learning_rate)
|
|
|
|
# Select your loss function
|
|
loss = tf.keras.losses.CategoricalCrossentropy(
|
|
from_logits=True, reduction=tf.losses.Reduction.NONE)
|
|
|
|
# Compile your model
|
|
model.compile(optimizer=optimizer, loss=loss, metrics=['accuracy'])
|
|
|
|
# Fit your model
|
|
model.fit(train_data, train_labels,
|
|
epochs=epochs,
|
|
validation_data=(test_data, test_labels),
|
|
batch_size=batch_size)
|
|
</pre>
|
|
|
|
- classname: devsite-landing-row-100
|
|
- heading: TensorFlow Privacy
|
|
options:
|
|
- description-100
|
|
items:
|
|
- classname: devsite-landing-row-100
|
|
description: >
|
|
<p>
|
|
Tensorflow Privacy (TF Privacy) is an open source library developed by teams in
|
|
Google Research. The library includes implementations of commonly used TensorFlow
|
|
Optimizers for training ML models with DP. The goal is to enable ML practitioners
|
|
using standard Tensorflow APIs to train privacy-preserving models by changing only a
|
|
few lines of code.
|
|
</p>
|
|
<p>
|
|
The differentially private optimizers can be used in conjunction with high-level APIs
|
|
that use the Optimizer class, especially Keras. Additionally, you can find differentially
|
|
private implementations of some Keras models. All of the Optimizers and models can be found
|
|
in the <a href="../api_docs/python/tf_privacy">API Documentation</a>.</p>
|
|
</p>
|
|
|
|
- classname: devsite-landing-row-cards
|
|
items:
|
|
- heading: "Introducing TensorFlow Privacy"
|
|
image_path: /resources/images/tf-logo-card-16x9.png
|
|
path: https://blog.tensorflow.org/2019/03/introducing-tensorflow-privacy-learning.html
|
|
buttons:
|
|
- label: "Read on TensorFlow blog"
|
|
path: https://blog.tensorflow.org/2019/03/introducing-tensorflow-privacy-learning.html
|
|
- heading: "TensorFlow Privacy at TF Dev Summit 2020"
|
|
youtube_id: UEECKh6PLhI
|
|
buttons:
|
|
- label: Watch the video
|
|
path: https://www.youtube.com/watch?v=UEECKh6PLhI
|
|
- heading: "TensorFlow Privacy on GitHub"
|
|
image_path: /resources/images/github-card-16x9.png
|
|
path: https://github.com/tensorflow/privacy
|
|
buttons:
|
|
- label: "View on GitHub"
|
|
path: https://github.com/tensorflow/privacy
|