[사내정보방열기] #7 ML, AWS, DATA

https://aws.amazon.com/ko/blogs/machine-learning/enhanced-text-classification-and-word-vectors-using-amazon-sagemaker-blazingtext/?nc1=h_ls

Enhanced text classification and word vectors using Amazon SageMaker BlazingText | Amazon Web Services

https://www.slideshare.net/nakjookwon5/aws-data-lake?next_slideshow=1

AWS 활용한 Data Lake 구성하기

https://www.slideshare.net/nakjookwon5/aws-digital

분석가를 위한 Aws 기반의 digital 플랫폼 구축

https://tfhub.dev/google/collections/bert/1

TensorFlow Hub

bert 모델들

https://tfhub.dev/s?q=text%20embedding

TensorFlow Hub

text embedding 모델들

https://github.com/keithrozario/Klayers/blob/master/deployments/python3.7/arns/us-west-1.csv

keithrozario/Klayers

aws arns us-west-1 모음 

lambda layers 에서 해당 arn 입력해서 패키지 추가하면 편함. 

https://aws.amazon.com/ko/blogs/korea/build-a-serverless-frontend-for-an-amazon-sagemaker-endpoint/

Amazon SageMaker를 위한 서버리스 엔드포인트 만들기 | Amazon Web Services

sagemaker로 서버리스 엔드포인트 만들기 

http://labs.brandi.co.kr/2019/10/04/dev1team.html

개발1팀의 AWS Personalize 도전기

aws personalize 를 이용해 개인화 상품추천 구현 

http://labs.brandi.co.kr/2020/01/28/kimwk.html

http://labs.brandi.co.kr/2020/01/28/kimwk.html

https://docs.aws.amazon.com/sagemaker/latest/dg/semantic-segmentation.html

Semantic Segmentation Algorithm - Amazon SageMaker

sagemaker를 이용해 semantic segmantation 구현

https://www.slideshare.net/awskr/amazoncom-129165538

Amazon.com 의 개인화 추천 / 예측 기능을 우리도 써 봅시다. :: 심호진 - AWS Community Day 20…

aws  personalize 대략적인 설명이 잘 되어있음. 

https://docs.aws.amazon.com/lambda/latest/dg/gettingstarted-limits.html

AWS Lambda limits - AWS Lambda

aws lambda 각종 제한들