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adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

ai_supermario

강화학습을 이용한 슈퍼마리오 만들기 튜토리얼 입니다.

aks-flask1

aks-flask2

ansible-examples

A few starter examples of ansible playbooks, to show features and how they work together. See http://galaxy.ansible.com for example roles from the Ansible community for deploying many popular applications.

ansible_course

Ansible Study Example

ansible_quickstart

This is scripts for making environment.

automl-gs

Provide an input CSV and a target field to predict, generate a model + code to run it.

avocado2018

OXQuiz Minigame

awesome-decision-tree-papers

A collection of research papers on decision, classification and regression trees with implementations.

awesome-recsys

Recommender Systems 에 관련된 논문을 정리하고 있습니다.

aws-kubeadm-terraform

create kubernetes cluster on AWS only typing 'terraform apply' on 3 minutes.

aws-provisioning

To provision AWS resources

awskrug-enterprise-workshop-2018

Learn to deploy real applications in a scalable way, using Amazon Web Services.

awsserverlesshol-ci-cd

Serverless HandsOnLab utilizing API GW, Polly, Lambda and CI/CD with CodeStar and Cloud9

bcafferky-shared

Code and shared files

cka

codespaces-with-copilot-sample

course-material

Updated Course Material for in28minutes courses on Java, Spring Boot, DevOps, AWS, Google Cloud and Azure.

cpp-doom

C++ Doom is a C++ fork of Crispy Doom 5.7.2 which is a limit-removing enhanced-resolution Doom source port based on Chocolate Doom.

csgm

Code to reproduce results from the paper: "Compressed Sensing using Generative Models".

data-engineering

data-science--cheat-sheet

Cheat Sheets

data-science-from-scratch

code for Data Science From Scratch book

deep-learning-notes

Experiments with Deep Learning

deeplearning-models

A collection of various deep learning architectures, models, and tips

devops

devops-box

A vagrant project with an ubuntu box with the tools needed to do DevOps

devopskoreahol

A repository for an Azure DevOps Hands-on-Lab with https://dev.azure.com/devopskr/DevOps_KOREA

docker

docker study.