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Vincent Granville
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  • Issaquah, WA
  • United States
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Vincent Granville posted a blog post
9 hours ago
Vincent Granville posted a blog post

Ten Simple Rules for Effective Statistical Practice

This article, written by Kass RE, Caffo BS, Davidian M, Meng X-L, Yu B, and Reid N, contains the following rules:Statistical Methods Should Enable Data to Answer Scientific QuestionsSignals Always Come with NoisePlan Ahead, Really AheadWorry about Data QualityStatistical Analysis Is More Than a Set of ComputationsKeep it SimpleProvide Assessments of VariabilityCheck Your AssumptionsWhen Possible, Replicate!The read the long and detailed article, and find out about rule #10,…See More
Tuesday
David Portabella replied to Vincent Granville's discussion History, Evolution and Classification of Programming Languages
"The wikipedia article about programming languages contains links to classifications and other data you might be interested: https://en.wikipedia.org/wiki/Programming_language "
Jan 6
Vincent Granville's discussion was featured

Challenge: Representation of Numbers as Infinite Products

This is our new challenge of the week. Previous challenges can be found here. While infinite products are equivalent to infinite sums when you take the logarithm, here we are interested in off-the-beaten-path, intriguing facts related to some special infinite products representations. Some of the questions raised here are very difficult.   …See More
Jan 4

Profile Information

Short Bio:
Well rounded, visionary data science executive with broad spectrum of domain expertise, technical knowledge, and proven success in bringing measurable added value to companies ranging from startups to fortune 100, across multiple industries (finance, Internet, media, IT, security) and domains (data science, operations research, machine learning, computer science, business intelligence, statistics, applied mathematics, growth hacking, IoT).

Vincent developed and deployed new techniques such as hidden decision trees (for scoring and fraud detection), automated tagging, indexing and clustering of large document repositories, black-box, scalable, simple, noise-resistant regression known as the Jackknife Regression (fit for black-box, real-time or automated data processing), model-free confidence intervals, bucketisation, combinatorial feature selection algorithms, detecting causation not correlations, and generally speaking, the invention of a set of consistent robust statistical / machine learning techniques that can be understood, implemented, interpreted, leveraged and fine-tuned by the non-expert. Vincent also invented many synthetic metrics (for instance, predictive power and L1 goodness-of-fit) that work better than old-fashioned stats, especially on badly-behaved sparse big data. Some of these techniques have been implemented in a Map-Reduce Hadoop-like environment. Some are concerned with identifying true signal in an ocean of noisy data.

Vincent is a former post-doctorate of Cambridge University and the National Institute of Statistical Sciences. He was among the finalists at the Wharton School Business Plan Competition and at the Belgian Mathematical Olympiads. Vincent has published 40 papers in statistical journals (including Journal of Number Theory, IEEE Pattern analysis and Machine Intelligence, Journal of the Royal Statistical Society, Series B), a Wiley book on data science, and is an invited speaker at international conferences. Vincent also created the first IoT platform to automate growth and content generation for digital publishers, using a system of API's for machine-to-machine communications, involving Hootsuite, Twitter, and Google Analytics.

Vincent's profile is accessible at http://bit.ly/1jWEfMP and includes top publications, presentations, and work experience with Visa, Microsoft, eBay, NBC, Wells Fargo, and other organisations.
My Website or LinkedIn Profile (URL):
http://www.linkedin.com/in/vincentg
Field of Expertise:
Data Mining, Marketing Databases, Web Analytics, Statistical Consulting, Other
Years of Experience in Analytical Role:
15+
Professional Status:
C-Level
Interests:
Networking, New Venture, Other
What is your Favorite Data Mining or Analytical Website?
http://www.analyticbridge.com
What Other Analytical Website do you Recommend?
http://www.datasciencecentral.com
Your Company:
Data Shaping Solutions
Industry:
Internet
How did you find out about AnalyticBridge?
Founder

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Vincent Granville's Blog

46 SQL Job Interview Questions for Data Scientists

Here is our updated selection of featured articles and resources posted over the weekend:

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Posted on January 15, 2017 at 7:49pm

Ten Simple Rules for Effective Statistical Practice

This article, written by Kass RE, Caffo BS, Davidian M, Meng X-L, Yu B, and Reid N, contains the following rules:

  • Statistical Methods Should Enable Data to Answer Scientific Questions
  • Signals Always Come with Noise
  • Plan Ahead, Really Ahead
  • Worry about Data Quality
  • Statistical Analysis Is More Than a Set of Computations
  • Keep it Simple
  • Provide Assessments of Variability
  • Check Your Assumptions
  • When Possible,…
Continue

Posted on January 10, 2017 at 11:16am

Are Lottery Winning Numbers Really Random?

Most analytic people would agree that lottery is a tax on the innumerate. However, for this statement to be true, we need to assume that winning numbers (and any combination of digits from these numbers) are truly random. If not, of course smart people are going to find and devise algorithms to increase their odds of winning, and/or will try to sell their magic "winning numbers" to idiots. …

Continue

Posted on December 23, 2016 at 8:30pm — 7 Comments

The Fundamental Statistics Theorem Revisited

In this article, we revisit the most fundamental statistics theorem, talking in layman terms. We investigate a special but interesting and useful case, that is not discussed in textbooks, data camps, or data science classes. This article is part of a series about off-the-beaten-path data science and mathematics, offering a fresh, original and simple perspective on a number of topics. Previous articles in this series can be found …

Continue

Posted on December 6, 2016 at 11:32am

Great Saturday Reading

Here is our selection of featured articles and resources, published in the last few days:

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Posted on December 3, 2016 at 2:43pm

Comment Wall (79 comments)

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At 1:15am on June 24, 2013, Hina Ranglani said…
sir,looking for a answer how
scaling up for high dimensional data& high speed data streams..
At 4:07am on April 12, 2013, Nene Lawani said…
Thanks Vincent! Sorry I missed this earlier...
At 4:06pm on March 10, 2013, Serge Kozlov said…

Thanks for the invite!

At 10:52am on March 10, 2013, Robert Downing said…

Thanks for the invite!

At 3:41am on March 9, 2013, Shane Campbell said…

vincent, 

thanks for adding me. can i ask you why you choose to add people like me? didn't see it coming?

regards,

shane

At 11:23am on March 8, 2013, Madhusudan Dusi said…

Vincent

Thanks a ton for the friendship, it matters a lot, so happy to accept your hand of friendship

Cheers & Regards

Madhusudan

At 6:37am on February 21, 2013, hunter.robertallan said…

Thanks also for the invite. I do have a question about data mining methods and tools. I have a specific situation in mind at work, and would like some professional feedback. Anyone willing to lend an ear and opinion..? thanks...rob

At 4:01am on February 17, 2013, Rishi Jain said…

Hey Vincent,

 

Sometime back I saw internship material on your site. I am working in the Analytics Industry and looking for improving my technical skills. Please let me know in case you guys are offering any internships which I can pursue along with my job.

Regards,

Rishi

At 3:04pm on December 19, 2012, Vickie Comrie said…

Thanks Vincent!  I am honored to be your friend.

Cheers,

Vickie

At 1:05pm on September 29, 2012, Ankit Sharma said…

Thank you Vincent. 

 
 
 

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