Personal Information
Organização/Local de trabalho
San Francisco Bay Area United States
Cargo
Data Scientist
Setor
Technology / Software / Internet
Sobre
Lead a team of researchers to perform statistical analysis and machine learning on large online ad serving data, using Hadoop platform + Python/R stack. Formulated and solved key business problems in three areas: (1) audience analytics, (2) user-based predictive modeling for conversions and clicks, and (3) ad-hoc analysis for internal and external clients. Focus has been: actionable results; high-quality research codes and presentations; reproducible research; single source of truth; open, collaborative, and agile research / development process.
Marcadores
r
statistics
데이터 사이언스
analytics
big data
데이터 과학
data science
unix
machine learning
best practice
storytelling
iris data
rstudio
sublime
에디터
툴채인
검색
영어
통계학
실리콘 밸리
hadoop
online advertising
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Apresentações
(7)Gostaram
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Ten Reasons Developers Hate Your API
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Fundamentals of Design for Non-Designers
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How To Analyze Geolocation Data with Hive and Hadoop
Hortonworks
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•
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Building Better Analytics Workflows (Strata-Hadoop World 2013)
Wes McKinney
•
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25 KPIs Every Manager Needs To Know
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•
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Developing Metrics and KPI (Key Performance Indicators
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Spatial Analysis with R - the Good, the Bad, and the Pretty
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Geospatial Data in R
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Intro to Spark and Spark SQL
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Lee Ji Eun
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pyrasis
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데이나의 참쉬운 애드테크 (20150419)
Dana Jeong
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Streaming Big Data with Spark, Kafka, Cassandra, Akka & Scala (from webinar)
Helena Edelson
•
Há 8 anos
[H3 2012] 꽃보다 Scala
KTH, 케이티하이텔
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Why Scala Is Taking Over the Big Data World
Dean Wampler
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국민대학교 컴퓨터프로그래밍
Minsuk Lee
•
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AWS를 활용하여 Daily Report 만들기 : 로그 수집부터 자동화된 분석까지
Changje Jeong
•
Há 8 anos
Real-Time Video Analytics Using Hadoop and HBase (HBaseCon 2013)
Suman Srinivasan
•
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차원축소 훑어보기 (PCA, SVD, NMF)
beom kyun choi
•
Há 9 anos
Startup Exits: A Primer
Mark Suster
•
Há 10 anos
Personal Information
Organização/Local de trabalho
San Francisco Bay Area United States
Cargo
Data Scientist
Setor
Technology / Software / Internet
Sobre
Lead a team of researchers to perform statistical analysis and machine learning on large online ad serving data, using Hadoop platform + Python/R stack. Formulated and solved key business problems in three areas: (1) audience analytics, (2) user-based predictive modeling for conversions and clicks, and (3) ad-hoc analysis for internal and external clients. Focus has been: actionable results; high-quality research codes and presentations; reproducible research; single source of truth; open, collaborative, and agile research / development process.
Marcadores
r
statistics
데이터 사이언스
analytics
big data
데이터 과학
data science
unix
machine learning
best practice
storytelling
iris data
rstudio
sublime
에디터
툴채인
검색
영어
통계학
실리콘 밸리
hadoop
online advertising
Ver mais