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amazon-kinesis-client-python

Amazon Kinesis Client Library for Python

azureml-mlflow-examples

chainer

A flexible framework of neural networks for deep learning

fastai

The fastai deep learning library, plus lessons and and tutorials

handsondeeplearningwithpytorch

Code snippets and applications explained in the book - HandsOnDeepLearningWithPytorch

interpret

Fit interpretable models. Explain blackbox machine learning.

interpret-community

Fit interpretable models with blackbox machine learning.

interpret-text-contrib

A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.

machinelearningnotebooks

Use the example notebooks in this repo to explore the Azure Machine Learning service.

materials

Bonus materials, exercises, and example projects for our Python tutorials

mlads2019

mlads2019fall-interpretability

This is a repo for use in our MLADs Lab in Fall 2019.

mlflow

Open source platform for the machine learning lifecycle

mmlspark

Microsoft Machine Learning for Apache Spark

msrest-for-python

The runtime library "msrest" for AutoRest generated Python clients.

nltk

NLTK Source

nltk_contrib

NLTK Contrib

opendifferentialprivacy.github.io

pydotfiles

Dotfile management made easy

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-dp

Training PyTorch models with differential privacy

requests

Python HTTP Requests for Humans™ ✨🍰✨

smartnoise-samples

Code samples and documentation for SmartNoise differential privacy tools

smartnoise-sdk

Tools and service for differentially private processing of tabular and relational data

spark

Mirror of Apache Spark

spark-install

Cross-platform installer for Apache Spark

sprint_gan

Privacy-preserving generative deep neural networks support clinical data sharing

training

Reference implementations of training benchmarks

trainingwheels

A debugging library for python

whitenoise-core

Differential privacy validator, runtime and language bindings