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Kumaran Ponnambalam
  • Male
  • Cupertino, CA
  • United States
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Kumaran Ponnambalam's Discussions

K Means Clustering - Effect of random seed

Started this discussion. Last reply by Adam Alloul Sep 28. 1 Reply

When the k-means clustering algorithm runs, it uses a randomly generated seed to determine the starting centroids of the clusters. …Continue

Estimating Data Science Projects

Started this discussion. Last reply by Phil Hummel Mar 2, 2016. 3 Replies

Data Science Projects are initiated by organizations with a specific goal and the sponsors of such projects would want a timeline in which the results need to be achieved. Data Science projects are…Continue

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Kumaran Ponnambalam's Page

Profile Information

Short Bio
I am data science practitioner currently leading Customer Interaction Advisor Projects at Broadsoft. I am involved in analyzing customer interactions data and finding ways to improve sales and customer service for our customers. I also love to write and teach
My Web Site Or LinkedIn Profile
http://www.linkedin.com/pub/kumaran-ponnambalam/4/a34/961
Field of Expertise
Analytics, Data Integration, Visualization, BI, Big Data, Data Science
Professional Status
Manager
Years of Experience:
21
Your Company:
Broadsoft Inc
Industry:
IT, SaaS, Analytics as a Service
Your Job Title:
Senior Director
How did you find out about DataScienceCentral?
Linked in
Interests:
Finding a new position, Networking
What is your Favorite Data Mining or Analytical Website?
http://datascientistinsights.com/

Kumaran Ponnambalam's Blog

Predictive Analytics for Unified Communications

Posted on March 30, 2016 at 4:30pm 0 Comments

More and more organizations today are moving to unified communications (UC) platforms for better communications within their organization, with their customers and with their partners. These platforms combine voice, email, chat and web into a seamless Omni-channel experience for its users. They today boost of a number of features, but most of them provide either static or rule based experiences. Given that these platforms generate tons of data, can this data be used to improve user…

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Apache Spark and R : The best of both worlds.

Posted on March 8, 2016 at 10:04am 1 Comment

As folks working in the field of Data Science and Analytics would know, R is one of the best languages to do data analytics and machine learning. Its simple and easy to use syntax and support for a huge library of capabilities makes it a top Data Science language. But the biggest limitation of R is the amount of data it can process. Its data processing capacity is limited to memory on a single node (at least the free version.).

Apache Spark is taking the Big…

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Impact of target class proportions on accuracy of classification

Posted on March 20, 2015 at 12:00pm 5 Comments

When we try to build classification models from training data, the proportion of target classes do impact the accuracy levels of predictions. This is an experiment to measure the level of impact of these proportions.



Let us say you are trying to predict which visitors to your website would buy a product. You collect historical data about the visitor's characteristics and actions and also whether they brought something or not. This is the model building data…

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Popular Software Skills in Data Science Job postings.

Posted on November 21, 2014 at 1:30pm 3 Comments

This exercise was done to understand the software skills that are in high demand for Data Science. Analysis was done by extracting the job postings from popular online websites. The findings are interesting. R continues to be the most popular skill, found in 70% of the postings. Python follows as a close second. Surprisingly, in spite all the talk about "Big Data Science", SQL comes up third. This shows that traditional RDBMS still continue to be the base for machine learning work…

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