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Eddie Soong
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  • Ontario
  • Canada
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Profile Information

Short Bio
Principal at Alexis Data Science
Alexis Data Science provides analytics products and services to small and medium companies in various industries to help them stay competitive through deep data insights
I am also a member of Zementis helping companies boost the performance of R and accelerating the deployment of models to the enterprise.
My Web Site Or LinkedIn Profile
http://https://www.linkedin.com/profile/view?id=2186555&trk=nav...
Professional Status
Other
Years of Experience:
10+
Your Company:
Zementis, Inc.
Industry:
Big Data Analytics
How did you find out about DataScienceCentral?
Google
Interests:
Networking, Recruiting, Other
What is your Favorite Data Mining or Analytical Website?
http://www.r-statistics.com/tag/r-community/
What Other Analytical Website do you Recommend?
http://www.inside-r.org/

Eddie Soong's Blog

The Three Pillars of Insurance Analytics

Posted on July 15, 2015 at 5:53am 0 Comments

Understanding the Role of Analytics in Insurance Industry

The insurance industry is all about assessing risk and managing the same successfully. Life insurance industry operates intrinsically by balancing risk assessment and risk management. Compiled with a large volume of…

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PMML - A good citizen of the Analytics Ecosystem

Posted on July 14, 2015 at 11:01am 0 Comments

As a data science professional how would you respond to the question, “How familiar are you with PMML?”

Your choices are:

-        “I have no idea what PMML is”

-        “I have heard and read about PMML”

-        “I have played around with PMML”

-        “I have used PMML in my projects”

I have seen many responses to the question and the most popular one was “I have no idea what PMML is”.

Is this surprising? I guess, if we look at the…

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How to score data in Hadoop/Hive in a flash

Posted on June 29, 2015 at 9:10pm 1 Comment

Reference to Hadoop implies huge amount of data. The intend of the data is of course to derive insights that will help businesses stay competitive. "Scoring" the data is a common exercise in determining e.g. customer churn, fraud detection, risk mitigation, etc... It is one of the slowest analytics activities and especially when very large data set is involved. There are various fast scoring products in the market but they are very specialized and/or are provided by one vendor, usually…

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Statistical Modeling steps

Posted on June 29, 2015 at 8:03pm 0 Comments

I'm a visual kind of guy. You've probably read various descriptions of the steps involved in building a statistical model. Here is a graphical version which I like. Hope you will enjoy it too. Courtesy of my friends at www.aureusanalytics.com, a big data analytics platform and solution company for Banking and Insurance.…

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