Brian Wang
0 SlideShares 2 Painéis de recortes 20 Seguidores 23 Seguindos
Personal Information
Organização/Local de trabalho
San Francisco Bay Area United States
Cargo
Senior Data Scientist at Oracle Adaptive Intelligent Applications
Setor
Advertising / Marketing / PR
Site
https://brianwang.youcanbook.me/
Sobre
Experienced Full Stack Senior Data Scientist in Recommender Systems, Marketing Automation, Predictive Modeling, Machine Learning, Lead Scoring, Data Mining, Big Data Analytics, Information Retrieval and Cold Start Project. Interested in using latest machine learning approaches, including FTRL, Factorization Machines, Bandit, Ensemble, AutoML, Tensorflow technologies to crack critical business challenges. Developing next generation Webscale Real Time Recommendation Algorithm for various applications.
Detalhes do contato
Gostaram (16)
Ver tudo
Deep Learning for Recommender Systems - Budapest RecSys Meetup
Alexandros Karatzoglou • Há 6 anos
Notes from Coursera Deep Learning courses by Andrew Ng
Tess Ferrandez • Há 4 anos
Recommender System with Distributed Representation
Rakuten Group, Inc. • Há 7 anos
Feature engineering-ml-meetup2-170220185754
Sergey Makarevich • Há 5 anos
Efficient Data Storage for Analytics with Apache Parquet 2.0
Cloudera, Inc. • Há 8 anos
Machine Learning and Data Mining: 14 Evaluation and Credibility
Pier Luca Lanzi • Há 15 anos
Bayesian Personalized Ranking for Non-Uniformly Sampled Items
Zeno Gantner • Há 11 anos
Business Applications of Predictive Modeling at Scale - KDD 2016 Tutorial
Qiang Zhu • Há 6 anos
[系列活動] 手把手的深度學習實務
台灣資料科學年會 • Há 6 anos
Social Party 分享: 從眾效應真的存在嗎？ Social Influence Bias: A Randomized Experiment
小均 張 • Há 8 anos
Chapter - 8.1 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
error007 • Há 9 anos
Factorization Machines with libFM
Liangjie Hong • Há 10 anos
Mobile Is Eating the World (2015)
a16z • Há 7 anos
Culture
Reed Hastings • Há 13 anos
Big Data and Advanced Analytics
McKinsey on Marketing & Sales • Há 9 anos
Analysis of financial performance for Alphabet (Google)
Mekko Graphics • Há 6 anos
Gostaram (16)
Ver tudo
Deep Learning for Recommender Systems - Budapest RecSys Meetup
Alexandros Karatzoglou • Há 6 anos
Notes from Coursera Deep Learning courses by Andrew Ng
Tess Ferrandez • Há 4 anos
Recommender System with Distributed Representation
Rakuten Group, Inc. • Há 7 anos
Feature engineering-ml-meetup2-170220185754
Sergey Makarevich • Há 5 anos
Efficient Data Storage for Analytics with Apache Parquet 2.0
Cloudera, Inc. • Há 8 anos
Machine Learning and Data Mining: 14 Evaluation and Credibility
Pier Luca Lanzi • Há 15 anos
Bayesian Personalized Ranking for Non-Uniformly Sampled Items
Zeno Gantner • Há 11 anos
Business Applications of Predictive Modeling at Scale - KDD 2016 Tutorial
Qiang Zhu • Há 6 anos
[系列活動] 手把手的深度學習實務
台灣資料科學年會 • Há 6 anos
Social Party 分享: 從眾效應真的存在嗎？ Social Influence Bias: A Randomized Experiment
小均 張 • Há 8 anos
Chapter - 8.1 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
error007 • Há 9 anos
Factorization Machines with libFM
Liangjie Hong • Há 10 anos
Mobile Is Eating the World (2015)
a16z • Há 7 anos
Culture
Reed Hastings • Há 13 anos
Big Data and Advanced Analytics
McKinsey on Marketing & Sales • Há 9 anos
Analysis of financial performance for Alphabet (Google)
Mekko Graphics • Há 6 anos
Personal Information
Organização/Local de trabalho
San Francisco Bay Area United States
Cargo
Senior Data Scientist at Oracle Adaptive Intelligent Applications
Setor
Advertising / Marketing / PR
Site
https://brianwang.youcanbook.me/
Sobre
Experienced Full Stack Senior Data Scientist in Recommender Systems, Marketing Automation, Predictive Modeling, Machine Learning, Lead Scoring, Data Mining, Big Data Analytics, Information Retrieval and Cold Start Project. Interested in using latest machine learning approaches, including FTRL, Factorization Machines, Bandit, Ensemble, AutoML, Tensorflow technologies to crack critical business challenges. Developing next generation Webscale Real Time Recommendation Algorithm for various applications.
Detalhes do contato