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Korea Korea, South
Occupation
software engineer at kakao
Website
brunch.co.kr/@goodvc78
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My identity is RecSys knowledge, Sense for data analysis, Fastest learning curve, Enjoy my jobs
The fully experience of Recsys in live service.
Tags
추천시스템
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recommender system
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t-sne
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#feature visualization
데이터야놀자
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파이썬분석
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recsys
word2vec
recommendersystem similarity
personal analytics
추천아 놀자
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추천
See more
Presentations
(15)
See all
Likes
(148)
See all
Engagement, Metrics & Personalisation at Scale
Mounia Lalmas-Roelleke
•
2 years ago
LinkedIn talk at Netflix ML Platform meetup Sep 2019
Faisal Siddiqi
•
3 years ago
Digital 2020 Global Digital Overview (January 2020) v01
DataReportal
•
3 years ago
아이템 추천의 다양성을 높이기 위한 후처리 방법(논문 리뷰)
hyunsung lee
•
5 years ago
The difference between lean back and lean forward
Own Company
•
9 years ago
Digital Revolution and Consumer Behaviour
Own Company
•
9 years ago
Data council SF 2020 Building a Personalized Messaging System at Netflix
Grace T. Huang
•
2 years ago
데이터를 얻으려는 노오오력
Youngjae Kim
•
5 years ago
Recent Trends in Personalization at Netflix
Justin Basilico
•
2 years ago
Lessons learned from building practical deep learning systems
Xavier Amatriain
•
3 years ago
SXSW2017 @NewDutchMedia Talk: Exploration is the New Search
Lora Aroyo
•
5 years ago
Tutorial on Online User Engagement: Metrics and Optimization
Mounia Lalmas-Roelleke
•
3 years ago
RecSys 2020 A Human Perspective on Algorithmic Similarity Schendel 9-2020
Zachary Schendel
•
2 years ago
Beyond DAUs and MAUs, 3 Key Levers to Understanding User Engagement For Your Mobile Apps
CleverTap
•
3 years ago
Facebook prophet
Minho Lee
•
5 years ago
Is Growth Important? Yes. But Retention Is King
TheFamily
•
8 years ago
Software-as-a-Service (SaaS) Secrets to Raising Venture Capital
Mamoon Hamid
•
7 years ago
The Holy Grail of Traction - Brian Balfour, HubSpot
Traction Conf
•
7 years ago
Measuring user engagement: the do, the do not do, and the we do not know
Mounia Lalmas-Roelleke
•
8 years ago
Personalizing the listening experience
Mounia Lalmas-Roelleke
•
3 years ago
A/B 테스트를 적용하기 어려울 때, 이벤트 효과 추정하기 (2020-01-18 잔디콘)
Minho Lee
•
3 years ago
Engagement, metrics and "recommenders"
Mounia Lalmas-Roelleke
•
3 years ago
Calibrated Recommendations
Harald Steck
•
4 years ago
Search-Based Serving Architecture of Embeddings-Based Recommendations (RecSys 2019)
Sonya Liberman
•
3 years ago
Recent Trends in Personalization: A Netflix Perspective
Justin Basilico
•
3 years ago
A Multi-Armed Bandit Framework For Recommendations at Netflix
Jaya Kawale
•
4 years ago
2019 cvpr paper_overview
LEE HOSEONG
•
3 years ago
Word2Vec Network Structure Explained
Subhashis Hazarika
•
4 years ago
Visualizing Data Using t-SNE
David Khosid
•
7 years ago
Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence
Dawen Liang
•
6 years ago
Adaptation and Evaluation of Recommendationsfor Short-term Shopping Goals
LukasLerche
•
7 years ago
Steffen Rendle, Research Scientist, Google at MLconf SF
MLconf
•
8 years ago
딥러닝 기본 원리의 이해
Hee Won Park
•
5 years ago
Notes from Coursera Deep Learning courses by Andrew Ng
Tess Ferrandez
•
4 years ago
Déjà Vu: The Importance of Time and Causality in Recommender Systems
Justin Basilico
•
5 years ago
Ensemble Contextual Bandits for Personalized Recommendation
Liang Tang
•
7 years ago
Wasserstein GAN 수학 이해하기 I
Sungbin Lim
•
5 years ago
CF Models for Music Recommendations At Spotify
Vidhya Murali
•
7 years ago
Session-Based Recommender Systems
Eötvös Loránd University
•
5 years ago
Recent Trends in Deep Learning
Sungjoon Choi
•
5 years ago
스타트업 인턴 개발자 3달간의 고군분투기 김은향
Eunhyang Kim
•
5 years ago
Growth Hacking with Predictive Analytics
Andrew Ahn
•
7 years ago
Jupyter notebook 이해하기
Yong Joon Moon
•
6 years ago
Deep learning text NLP and Spark Collaboration . 한글 딥러닝 Text NLP & Spark
hoondong kim
•
5 years ago
RecSys 2015 - Unifying the Problem of Search and Recommendations at OpenTable
Jeremy Schiff
•
7 years ago
악평생성기 (Bad Comment Generator using RNN) _ 송치성
Chisung Song
•
6 years ago
Detection of fashion trends and seasonal cycles using client feedback
Roberto Sanchis Ojeda
•
6 years ago
Data Day Texas 2017: Scaling Data Science at Stitch Fix
Stefan Krawczyk
•
6 years ago
(Some) pitfalls of distributed learning
Yves Raimond
•
6 years ago
[214]베이지안토픽모형 강병엽
NAVER D2
•
6 years ago
[216]딥러닝예제로보는개발자를위한통계 최재걸
NAVER D2
•
6 years ago
Generative adversarial networks
남주 김
•
6 years ago
Algorithmic Music Recommendations at Spotify
Chris Johnson
•
9 years ago
Recsys 2015: Making Meaningful Restaurant Recommendations at OpenTable
Sudeep Das, Ph.D.
•
7 years ago
word2vec-DataPalooza-Seattle
castanan2
•
6 years ago
Meta-Prod2Vec: Simple Product Embeddings with Side-Information
recsysfr
•
6 years ago
What is word2vec?
Traian Rebedea
•
7 years ago
Latent Semanctic Analysis Auro Tripathy
Auro Tripathy
•
10 years ago
It's Not Magic - Explaining classification algorithms
Brian Lange
•
6 years ago
data science @NYT ; inaugural Data Science Initiative Lecture
chris wiggins
•
7 years ago
Recsys 2016 tutorial: Lessons learned from building real-life recommender systems
Xavier Amatriain
•
6 years ago
Past present and future of Recommender Systems: an Industry Perspective
Xavier Amatriain
•
6 years ago
Gaussian Ranking by Matrix Factorization, ACM RecSys Conference 2015
Harald Steck
•
7 years ago
지적 대화를 위한 깊고 넓은 딥러닝 PyCon APAC 2016
Taehoon Kim
•
6 years ago
Drawing word2vec
Kai Sasaki
•
8 years ago
Lessons learnt at building recommendation services at industry scale
Domonkos Tikk
•
6 years ago
Customer Retention Rate Analysis
RetentionLogix
•
10 years ago
2016 kcd 세미나 발표자료. 구글포토로 바라본 인공지능과 머신러닝
JungGeun Lee
•
7 years ago
파이썬+주요+용어+정리 20160304
Yong Joon Moon
•
6 years ago
Slow date project
Hanyang University
•
7 years ago
word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
👋 Christopher Moody
•
7 years ago
word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
👋 Christopher Moody
•
7 years ago
시나브로 배우는 자연어처리 바벨피쉬 송치성
Chisung Song
•
7 years ago
Allison Gilmore, Data Scientist, Ayasdi at MLconf SF - 11/13/15
MLconf
•
7 years ago
10 more lessons learned from building Machine Learning systems
Xavier Amatriain
•
7 years ago
From Idea to Execution: Spotify's Discover Weekly
Chris Johnson
•
7 years ago
Music Personalization : Real time Platforms.
Esh Vckay
•
7 years ago
Lunch Club_Netflix Recommendations
StartupAlliance
•
8 years ago
집필방법론.V.1.2
Sangmin Lee
•
11 years ago
Linear models for data science
Brad Klingenberg
•
7 years ago
[IGC 2015] 지속가능한 개발팀..이란 꿈을 꾸었습니다
Hwang Sang Hun
•
7 years ago
20150306 파이썬기초 IPython을이용한프로그래밍_이태영
Tae Young Lee
•
7 years ago
Python Korea 2014년 6월 세미나 - Windows 환경에서 Python 개발환경 세팅하기
Joongi Kim
•
8 years ago
Approximate nearest neighbor methods and vector models – NYC ML meetup
Erik Bernhardsson
•
7 years ago
20150307 abcd발표_ux디자이너 실력으로 살아남기
SANGBUM HA
•
7 years ago
Interactive Recommender Systems with Netflix and Spotify
Chris Johnson
•
7 years ago
[151] 영상 인식을 통한 오프라인 고객분석 솔루션과 딥러닝
NAVER D2
•
7 years ago
QCon Rio - Machine Learning for Everyone
Dhiana Deva
•
7 years ago
도도와 파이썬: 좋은 선택과 나쁜 선택
Jc Kim
•
7 years ago
[PyConKR 2015] 라이트닝토크 - 어느 여자 개발자의 육아휴직 2년
Joeun Park
•
7 years ago
2015 py con word2vec이 추천시스템을 만났을때
choi kyumin
•
7 years ago
Machine Learning to Grow the World's Knowledge
Xavier Amatriain
•
7 years ago
[SmartNews] Globally Scalable Web Document Classification Using Word2Vec
Kouhei Nakaji
•
7 years ago
Word2Vec: Learning of word representations in a vector space - Di Mitri & Hermans
Daniele Di Mitri
•
7 years ago
Growing Your Business Through Experimentation
Hiten Shah
•
7 years ago
Full Text Search Throwdown
Karwin Software Solutions LLC
•
13 years ago
Information retrieval to recommender systems
Data Science Society
•
7 years ago
Spotify's Music Recommendations Lambda Architecture
Esh Vckay
•
7 years ago
집단지성 프로그래밍 02-추천시스템 만들기
Kwang Woo NAM
•
8 years ago
공공데이터 활용을 위한 "Tech 워크숍" 2회 - 공공데이터 수집, 가공하고 활용하기
Cheol Kang
•
8 years ago
[20140830, Pycon2014] NetworkX를 이용한 네트워크 분석
Kyunghoon Kim
•
8 years ago
elasticsearch_적용 및 활용_정리
Junyi Song
•
7 years ago
Mr. Presentation
Ethos3
•
14 years ago
빅데이터, 클라우드, IoT, 머신러닝. 왜 이렇게 많은 것들이 나타날까?
Yongho Ha
•
7 years ago
NDC 2015 이은석 - pay-to-skip: 온라인 게임 속 로봇 경제와 내몰리는 인간
Eunseok Yi
•
7 years ago
Collaborative filtering getting_started
Vivek Aanand Ganesan
•
9 years ago
Machine Learning for Recommender Systems MLSS 2015 Sydney
Alexandros Karatzoglou
•
7 years ago
Learning to Rank for Recommender Systems - ACM RecSys 2013 tutorial
Alexandros Karatzoglou
•
9 years ago
MLConf Seattle 2015 - ML@Quora
Xavier Amatriain
•
7 years ago
MLConf - Emmys, Oscars & Machine Learning Algorithms at Netflix
Xavier Amatriain
•
9 years ago
Bando de Dados Avançados - Recommender Systems
Gustavo Coutinho
•
7 years ago
금융 데이터 이해와 분석 PyCon 2014
Seung-June Lee
•
7 years ago
Word2vec algorithm
Andrew Koo
•
8 years ago
From A Neural Probalistic Language Model to Word2vec
Jungkyu Lee
•
8 years ago
실리콘 밸리 데이터 사이언티스트의 하루
Jaimie Kwon (권재명)
•
7 years ago
Scala Data Pipelines for Music Recommendations
Chris Johnson
•
8 years ago
10 Lessons Learned from Building Machine Learning Systems
Xavier Amatriain
•
8 years ago
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Lean Analytics
•
8 years ago
Music recommendations @ MLConf 2014
Erik Bernhardsson
•
8 years ago
Music Recommendations at Scale with Spark
Chris Johnson
•
8 years ago
앙상블 학습 기반의 추천시스템 개발
Jungkyu Lee
•
9 years ago
RecSysTEL lecture at advanced SIKS course, NL
Hendrik Drachsler
•
10 years ago
Deep Learning through Examples
Sri Ambati
•
8 years ago
Machine Learning & Recommender Systems at Netflix Scale
C4Media
•
9 years ago
Recsys 2014 Tutorial - The Recommender Problem Revisited
Xavier Amatriain
•
8 years ago
Recommender Systems (Machine Learning Summer School 2014 @ CMU)
Xavier Amatriain
•
8 years ago
How Google Works / 구글은 어떻게 일하는가 (Korean / 한국어 버전)
Mika Eunjin Kang
•
8 years ago
Datadesignmeaning
Idan Gazit
•
9 years ago
2.네이버 프론트엔드 김지태
NAVER D2
•
8 years ago
손코딩뇌컴파일눈디버깅을 소개합니다.
Kwangsung Ha
•
9 years ago
LUMA's The Future of (Digital) TV
LUMA Partners
•
8 years ago
Collaborative Filtering with Spark
Chris Johnson
•
8 years ago
Hello, Recommender System
Kyuhwan Jung
•
9 years ago
스타트업에서 기술책임자로 살아가기
Hyun-woo Park
•
8 years ago
KPCB Internet Trends 2013
Kleiner Perkins
•
9 years ago
How to Create an Early Stage Pitch Deck
Ryan Spoon
•
11 years ago
스타트업은 데이터를 어떻게 바라봐야 할까? (개정판)
Yongho Ha
•
8 years ago
svn 능력자를 위한 git 개념 가이드
Insub Lee
•
9 years ago
배달의 민족 브랜드 마케팅 이야기 by 우아한형제들 김봉진 대표
VentureSquare
•
9 years ago
Facebook, The Perfect Startup
Fabernovel
•
10 years ago
26 Time Management Hacks I Wish I'd Known at 20
Étienne Garbugli
•
9 years ago
오승준, 사회적 기술이 프로그래머 인생을 바꿔주는 이유, NDC2011
devCAT Studio, NEXON
•
11 years ago
플랫폼데이2013 workflow기반 실시간 스트리밍데이터 수집 및 분석 플랫폼 발표자료
choi kyumin
•
9 years ago
Presentations
(15)
See all
Likes
(148)
See all
Engagement, Metrics & Personalisation at Scale
Mounia Lalmas-Roelleke
•
2 years ago
LinkedIn talk at Netflix ML Platform meetup Sep 2019
Faisal Siddiqi
•
3 years ago
Digital 2020 Global Digital Overview (January 2020) v01
DataReportal
•
3 years ago
아이템 추천의 다양성을 높이기 위한 후처리 방법(논문 리뷰)
hyunsung lee
•
5 years ago
The difference between lean back and lean forward
Own Company
•
9 years ago
Digital Revolution and Consumer Behaviour
Own Company
•
9 years ago
Data council SF 2020 Building a Personalized Messaging System at Netflix
Grace T. Huang
•
2 years ago
데이터를 얻으려는 노오오력
Youngjae Kim
•
5 years ago
Recent Trends in Personalization at Netflix
Justin Basilico
•
2 years ago
Lessons learned from building practical deep learning systems
Xavier Amatriain
•
3 years ago
SXSW2017 @NewDutchMedia Talk: Exploration is the New Search
Lora Aroyo
•
5 years ago
Tutorial on Online User Engagement: Metrics and Optimization
Mounia Lalmas-Roelleke
•
3 years ago
RecSys 2020 A Human Perspective on Algorithmic Similarity Schendel 9-2020
Zachary Schendel
•
2 years ago
Beyond DAUs and MAUs, 3 Key Levers to Understanding User Engagement For Your Mobile Apps
CleverTap
•
3 years ago
Facebook prophet
Minho Lee
•
5 years ago
Is Growth Important? Yes. But Retention Is King
TheFamily
•
8 years ago
Software-as-a-Service (SaaS) Secrets to Raising Venture Capital
Mamoon Hamid
•
7 years ago
The Holy Grail of Traction - Brian Balfour, HubSpot
Traction Conf
•
7 years ago
Measuring user engagement: the do, the do not do, and the we do not know
Mounia Lalmas-Roelleke
•
8 years ago
Personalizing the listening experience
Mounia Lalmas-Roelleke
•
3 years ago
A/B 테스트를 적용하기 어려울 때, 이벤트 효과 추정하기 (2020-01-18 잔디콘)
Minho Lee
•
3 years ago
Engagement, metrics and "recommenders"
Mounia Lalmas-Roelleke
•
3 years ago
Calibrated Recommendations
Harald Steck
•
4 years ago
Search-Based Serving Architecture of Embeddings-Based Recommendations (RecSys 2019)
Sonya Liberman
•
3 years ago
Recent Trends in Personalization: A Netflix Perspective
Justin Basilico
•
3 years ago
A Multi-Armed Bandit Framework For Recommendations at Netflix
Jaya Kawale
•
4 years ago
2019 cvpr paper_overview
LEE HOSEONG
•
3 years ago
Word2Vec Network Structure Explained
Subhashis Hazarika
•
4 years ago
Visualizing Data Using t-SNE
David Khosid
•
7 years ago
Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence
Dawen Liang
•
6 years ago
Adaptation and Evaluation of Recommendationsfor Short-term Shopping Goals
LukasLerche
•
7 years ago
Steffen Rendle, Research Scientist, Google at MLconf SF
MLconf
•
8 years ago
딥러닝 기본 원리의 이해
Hee Won Park
•
5 years ago
Notes from Coursera Deep Learning courses by Andrew Ng
Tess Ferrandez
•
4 years ago
Déjà Vu: The Importance of Time and Causality in Recommender Systems
Justin Basilico
•
5 years ago
Ensemble Contextual Bandits for Personalized Recommendation
Liang Tang
•
7 years ago
Wasserstein GAN 수학 이해하기 I
Sungbin Lim
•
5 years ago
CF Models for Music Recommendations At Spotify
Vidhya Murali
•
7 years ago
Session-Based Recommender Systems
Eötvös Loránd University
•
5 years ago
Recent Trends in Deep Learning
Sungjoon Choi
•
5 years ago
스타트업 인턴 개발자 3달간의 고군분투기 김은향
Eunhyang Kim
•
5 years ago
Growth Hacking with Predictive Analytics
Andrew Ahn
•
7 years ago
Jupyter notebook 이해하기
Yong Joon Moon
•
6 years ago
Deep learning text NLP and Spark Collaboration . 한글 딥러닝 Text NLP & Spark
hoondong kim
•
5 years ago
RecSys 2015 - Unifying the Problem of Search and Recommendations at OpenTable
Jeremy Schiff
•
7 years ago
악평생성기 (Bad Comment Generator using RNN) _ 송치성
Chisung Song
•
6 years ago
Detection of fashion trends and seasonal cycles using client feedback
Roberto Sanchis Ojeda
•
6 years ago
Data Day Texas 2017: Scaling Data Science at Stitch Fix
Stefan Krawczyk
•
6 years ago
(Some) pitfalls of distributed learning
Yves Raimond
•
6 years ago
[214]베이지안토픽모형 강병엽
NAVER D2
•
6 years ago
[216]딥러닝예제로보는개발자를위한통계 최재걸
NAVER D2
•
6 years ago
Generative adversarial networks
남주 김
•
6 years ago
Algorithmic Music Recommendations at Spotify
Chris Johnson
•
9 years ago
Recsys 2015: Making Meaningful Restaurant Recommendations at OpenTable
Sudeep Das, Ph.D.
•
7 years ago
word2vec-DataPalooza-Seattle
castanan2
•
6 years ago
Meta-Prod2Vec: Simple Product Embeddings with Side-Information
recsysfr
•
6 years ago
What is word2vec?
Traian Rebedea
•
7 years ago
Latent Semanctic Analysis Auro Tripathy
Auro Tripathy
•
10 years ago
It's Not Magic - Explaining classification algorithms
Brian Lange
•
6 years ago
data science @NYT ; inaugural Data Science Initiative Lecture
chris wiggins
•
7 years ago
Recsys 2016 tutorial: Lessons learned from building real-life recommender systems
Xavier Amatriain
•
6 years ago
Past present and future of Recommender Systems: an Industry Perspective
Xavier Amatriain
•
6 years ago
Gaussian Ranking by Matrix Factorization, ACM RecSys Conference 2015
Harald Steck
•
7 years ago
지적 대화를 위한 깊고 넓은 딥러닝 PyCon APAC 2016
Taehoon Kim
•
6 years ago
Drawing word2vec
Kai Sasaki
•
8 years ago
Lessons learnt at building recommendation services at industry scale
Domonkos Tikk
•
6 years ago
Customer Retention Rate Analysis
RetentionLogix
•
10 years ago
2016 kcd 세미나 발표자료. 구글포토로 바라본 인공지능과 머신러닝
JungGeun Lee
•
7 years ago
파이썬+주요+용어+정리 20160304
Yong Joon Moon
•
6 years ago
Slow date project
Hanyang University
•
7 years ago
word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
👋 Christopher Moody
•
7 years ago
word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
👋 Christopher Moody
•
7 years ago
시나브로 배우는 자연어처리 바벨피쉬 송치성
Chisung Song
•
7 years ago
Allison Gilmore, Data Scientist, Ayasdi at MLconf SF - 11/13/15
MLconf
•
7 years ago
10 more lessons learned from building Machine Learning systems
Xavier Amatriain
•
7 years ago
From Idea to Execution: Spotify's Discover Weekly
Chris Johnson
•
7 years ago
Music Personalization : Real time Platforms.
Esh Vckay
•
7 years ago
Lunch Club_Netflix Recommendations
StartupAlliance
•
8 years ago
집필방법론.V.1.2
Sangmin Lee
•
11 years ago
Linear models for data science
Brad Klingenberg
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Personal Information
Organization / Workplace
Korea Korea, South
Occupation
software engineer at kakao
Website
brunch.co.kr/@goodvc78
About
My identity is RecSys knowledge, Sense for data analysis, Fastest learning curve, Enjoy my jobs
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