Personal Information
Unternehmen/Arbeitsplatz
Japan Japan
Beruf
Research Engineer
Branche
Technology / Software / Internet
Info
I had studied natural language processing in graduate school mostly focusing on information extraction and data mining.
Now I work as a data scientist analyzing data both internal and external and developing a data analysis platform.
Resume: https://sites.google.com/site/priancho/aboutme/cv
- Präsentationen
- Dokumente
- Infografiken
[NDC 2014] 모에론
Yongha Kim
•
Vor 9 Jahren
外の人が中から見たTohokuNLP
Ryoko Tokuhisa
•
Vor 2 Jahren
논문쓸 때 혼동하기 쉬운 단어들
에디티지(Editage Korea)
•
Vor 9 Jahren
[DL輪読会]Learning to Generalize: Meta-Learning for Domain Generalization
Deep Learning JP
•
Vor 6 Jahren
MLOps Using MLflow
Databricks
•
Vor 3 Jahren
Introducing MLflow for End-to-End Machine Learning on Databricks
Databricks
•
Vor 3 Jahren
Simplifying Model Management with MLflow
Databricks
•
Vor 4 Jahren
E-commerce BigData Scale AI Journey
hoondong kim
•
Vor 5 Jahren
[AI & DevOps] BigData Scale Production AI 서비스를 위한 최상의 플랫폼 아키텍처
hoondong kim
•
Vor 5 Jahren
MLFlow: Platform for Complete Machine Learning Lifecycle
Databricks
•
Vor 5 Jahren
Docker 로 Linux 없이 Linux 환경에서 개발하기
iFunFactory Inc.
•
Vor 7 Jahren
TF에서 팀 빌딩까지 9개월의 기록 : 성장하는 조직을 만드는 여정
Seongyun Byeon
•
Vor 4 Jahren
도커 무작정 따라하기: 도커가 처음인 사람도 60분이면 웹 서버를 올릴 수 있습니다!
pyrasis
•
Vor 9 Jahren
"simple does it weakly supervised instance and semantic segmentation" Paper review
LEE HOSEONG
•
Vor 5 Jahren
Matching networks for one shot learning
Kazuki Fujikawa
•
Vor 7 Jahren
소프트웨어 개발 프로세스 개선
Jung Dohyun
•
Vor 8 Jahren
KPTのコツを掴め!! 公開用
ESM SEC
•
Vor 8 Jahren
KPTは2回目が大切なのに…
Mineo Matsuya
•
Vor 5 Jahren
Distributed TensorFlow on Hadoop, Mesos, Kubernetes, Spark
Jan Wiegelmann
•
Vor 6 Jahren
Deep Learning 모델의 효과적인 분산 트레이닝과 모델 최적화 방법 - 김무현 데이터 사이언티스트, AWS :: AWS Summit Seoul 2019
Amazon Web Services Korea
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Vor 5 Jahren