Java based Convolutional Neural Network package running on Apache Spark framework
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Updated
Jan 14, 2017 - Java
Java based Convolutional Neural Network package running on Apache Spark framework
Java based Convolutional Neural Network package running on Apache Spark framework
mnist, using caffe and openmpi
TensorFlow (1.8+) Datasets, Feature Columns, Estimators and Distributed Training using Google Cloud Machine Learning Engine
Learn applied deep learning from zero to deployment using TensorFlow 1.8+
Collection of resources for automatic deployment of distributed deep learning jobs on a Kubernetes cluster
Simultaneous Multi-Party Learning Framework
PyTorch Examples for Beginners
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Horovod Tutorial for Pytorch using NVIDIA-Docker.
A Portable C Library for Distributed CNN Inference on IoT Edge Clusters
sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data
A blockchain based neural architecture search project.
WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can be initiated without requiring that all the processes enter it. It partially reduces the data within non-overlapping groups of process, improving the…
Yelp review classification using CNN model with horovod on HPC cluster
Distributed Tensorflow, Keras and BigDL on Apache Spark
Eager-SGD is a decentralized asynchronous SGD. It utilizes novel partial collectives operations to accumulate the gradients across all the processes.
An implementation of a distributed ResNet model for classifying CIFAR-10 and MNIST datasets.
This repository contains the implementation of a wide variety of Deep Learning Projects in different applications of computer vision, NLP, federated, and distributed learning. These projects include university projects and projects implemented due to interest in Deep Learning.
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