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pytorch-cnn-finetune

Fine-tune pretrained Convolutional Neural Networks with PyTorch

pytorch-lightning

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

pytorch_resnet_preact

A PyTorch implementation of ResNet-preact

pytorchnet

Generalized Framework for PyTorch

quantitative-big-imaging-2018

The material for the Quantitative Big Imaging course at ETHZ for the Spring Semester 2018

quantstack-talks

Slides for quantstack talks

rabit

Reliable Allreduce and Broadcast Interface for distributed machine learning

rapids_aip

ray

A high-performance distributed execution engine

resnext-pytorch

reverb

Reverb is an efficient and easy-to-use data storage and transport system designed for machine learning research

rl_a3c_pytorch

A3C LSTM Atari with Pytorch plus A3G design

rocksdb

A library that provides an embeddable, persistent key-value store for fast storage.

ruby-ex

scalable_agent

A TensorFlow implementation of Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.

scheduler-plugins

Repository for out-of-tree scheduler plugins based on scheduler framework.

seed_rl

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.

serving

Kubernetes-based, scale-to-zero, request-driven compute

slides

Slides from my presentations

smart-city-sample

The smart city reference pipeline shows how to integrate various media building blocks, with analytics powered by the OpenVINO™ Toolkit, for traffic or stadium sensing, analytics and management tasks.

smile

Statistical Machine Intelligence & Learning Engine

snappy-store

SnappyStore

snappydata

SnappyData - The Spark Database. Stream, Transact, Analyze, Predict in one cluster

spark-deep-learning

Deep Learning Pipelines for Apache Spark

spark-gpu

Spark GPU and SIMD Support

spark-overflow

A stack overflow for Apache Spark

spark-word2vec

A parallel implementation of word2vec based on Spark

sparkgpu

GPU* or SPARK* branches are used for generating GPU code in Tungsten/concact:@kiszk, MLlib branch is used for CUDA-MLlib project/concact:@bherta

spearmint

Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012

speedo

Parallelizing Stochastic Gradient Descent for Deep Convolutional Neural Network