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Interview: Paul Robbins, STATS on the Potential and Challenges for Sports Analytics
We discuss Analytics at STATS, typical daily tasks, ICE Analytics platform, key challenges, response from coaches/players, career advice and more.
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Hot or Not: Data Science Trends in 2015
CrowdFlower infographic predicts the hot trends for data science in 2015 and which trends will fade away.
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Interview: Brian Hampton, San Francisco 49ers on Playing Football the Analytics Way
We discuss the role of analytics in football, the underrated challenges, evolution since the era of draft trade value chart and analytics-supported team selection.
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Interview: Daqing Zhao, Macys.com on Building Effective Data Models for Marketing
We discuss the challenges in identifying the fair price of ad media, recommendations for building effective models for online marketing, unique challenges of Mobile channel, selection of Big Data tools, and more.
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Why Azure ML is the Next Big Thing for Machine Learning?
With advanced capabilities, free access, strong support for R, cloud hosting benefits, drag-and-drop development and many more features, Azure ML is ready to take the consumerization of ML to the next level.
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TweetNLP: Twitter Natural Language Processing
A short overview of Natural Language Processing tools and utilities developed by Prof. Noah Smith, CMU and his team to analyze Twitter data.
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Interview: Sastry Malladi, StubHub on Designing Big Data Architecture for the Unknown Future
By Anmol Rajpurohit on July 28, 2014 in Architecture, Challenges, Design, Hadoop, Interview, Metadata, Personalization, Recommendation, Sastry Malladi, StubHubWe discuss the Big Data architecture at StubHub, important factors in architecture design, hybrid approach of using Big Data along with traditional data warehouses, challenges, importance of meta-data and more.
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Interview: Samaneh Moghaddam, Applied Researcher, eBay on Opinion Mining – Typical Projects and Major Challenges
We discuss typical sentiment analysis problems at eBay, underrated challenges, career motivation, important soft skills and more.
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Interview: Kirk Borne, Data Scientist, GMU on Big Data in Astrophysics and Correlation vs. Causality
We discuss how to build the best data models, significance of correlation and causality in Predictive Analytics, and impact of Big Data on Astrophysics.
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Interview: Richard Wendell, VP, Data Science, TE Connectivity on Strategy for Analytics Projects
We discuss the last mile of the execution path of Analytics projects, five critical pillars of success and data-driven decision making through advanced analytics.
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