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amazon-dsstne

Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

cfncluster

CfnCluster is a framework that deploys and maintains HPC clusters on AWS.

cfncluster-cookbook

The Chef cookbook used to build and bootstrap CfnCluster

cfncluster-node

cfncluster-node is the python package installed on the Amazon EC2 instances launched as part of CfnCluster

deep-learning-containers

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

fabtests

A set of examples that uses Libfabric

funprograms

k8s-learn

learning

kubernetes-the-hard-way

Bootstrap Kubernetes the hard way on Vagrant on Local Machine. No scripts.

langchain

⚡ Building applications with LLMs through composability ⚡

langserve

LangServe 🦜️🏓

libfabric

Open Fabric Interfaces

locust

Scalable user load testing tool written in Python

ml-eng

This package is used to learn the basics of ml from engineering prespective

mpi

mtt

MPI Testing Tool

mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

ofi-guide

OFI Programmer's Guide

ompi

Open MPI main development repository

pmix

PMIx master repository

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

ray-files

sagemaker-distribution

A set of Docker images that include popular frameworks for machine learning, data science and visualization.

sagemaker-python-sdk

A library for training and deploying machine learning models on Amazon SageMaker