parandurume Goto Github PK

azurebot

first bot using azure bot framework

deep_learning

Deep Learning

demo-20180805-startup-dev

2018년 8월 5일, 서울창조허브 10F에서 열리는 개발기술연합세미나, 파이썬 세션, 장고 샘플 프로젝트

demo-azure-201810

지금은 Azure 시대! Azure의 정석

dialogflow-response-library-implementation-python-django

This repository is to demonstrate the implementation of our Dialogflow response library in Python and Django

drazure

exo-tool-kit

Tools to help along the journey becoming an ExO

flask

fulfillment-weather-python

Sample showing complex agent and fulfillment design

hol-azure-machine-learning

Introduction to Machine Learning and Azure Machine Learning Services. Hands on labs to show Azure Machine Learning features, developing experiments, feature engineering, R and Python Scripting, Production stage, publishing models as web service, RRS and BES usage

keraspp

코딩셰프의 3분 딥러닝, 케라스맛

kobart

Korean BART

kobert

Korean BERT pre-trained cased (KoBERT)

naver_movie

naver movie comment crawling (네이버 영화 평점 크롤링 감정분석 딥러닝을 위해)

parandurume.github.io

php-da-sample

power-automate-docs

powerapps-docs

Technical Documentation for Microsoft PowerApps

rest-api-sections

A small repository of projects built in my course, REST APIs with Flask and Python.

studyml

truechain-stellar

TrueChain Stellar run on Ethereum

vs-tools-for-ai

Visual Studio Tools for AI is a free Visual Studio extension to build, test, and deploy deep learning / AI solutions. It seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not limited to submitting data preparation and model training jobs transparently to different compute targets. Additionally, it provides support for custom metrics and run history tracking, enabling data science reproducibility and auditing. Enterprise ready collaboration, allow to securely work on project with other people.

vscode-tools-for-ai

VS Code Tools for AI is an extension to build, test, and deploy Deep Learning / AI solutions. It seamlessly integrates with Azure Machine Learning for robust experimentation capabilities, including but not limited to submitting data preparation and model training jobs transparently to different compute targets. Additionally, it provides support for custom metrics and run history tracking, enabling data science reproducibility and auditing. Enterprise ready collaboration, allow to securely work on project with other people.

wellnessconversation-languagemodel

Korean Language Model을 이용한 심리상담 대화 언어 모델.