Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS

Python Remote Administration Tool (RAT) to gain meterpreter session

A simple Python-Rootkit script

The vSphere tags Terraform module either creates or imports a tag category as well as a list of tags in your VMware Cloud on AWS or VMware vSphere on-premises environment, and then outputs the conf…

Terraform Module for create AWS IPAM Resources

The vSphere content library Terraform module either creates or imports a content library as well as a list of items in your VMware Cloud on AWS or VMware vSphere on-premises environment, and then o…

Terraform Module to deploy Route53 Application Recovery Controller components

AWS Global Network Module

AWS Control Tower Account Factory

AWS ECS Fargate Module

AWS ECS Fargate Module

AWS CodeBuild Module

The SageMaker Spark Container is a Docker image used to run data processing workloads with the Spark framework on Amazon SageMaker.

Docker images that replicate the Amazon SageMaker Notebook instance.

This project shows step-by-step guide on how to build a real-world flower classifier of 102 flower types using TensorFlow, Amazon SageMaker, Docker and Python in a Jupyter Notebook.

CLI for building Docker images in SageMaker Studio using AWS CodeBuild.

Docker container for running Chainer scripts to train and host Chainer models on SageMaker

This is the Docker container based on open source framework XGBoost (https://xgboost.readthedocs.io/en/latest/) to allow customers use their own XGBoost scripts in SageMaker.

This repository contains examples of Docker images that can be used as custom images for KernelGateway Apps in SageMaker Studio

Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.

Simple Python version management

Toolkit for running TensorFlow training scripts on SageMaker. Dockerfiles used for building SageMaker TensorFlow Containers are at https://github.com/aws/deep-learning-containers.

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

Code and associated files for the deploying ML models within AWS SageMaker

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

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

Django Boilerplate - Material Kit Design | AppSeed