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Vincent Granville
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  • Issaquah, WA
  • United States
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Parmod Kumar liked Vincent Granville's blog post High Precision Computing in Python or R
Tuesday
Vincent Granville posted a blog post

High Precision Computing in Python or R

Here we discuss an application of HPC (not high performance computing, instead high precision computing, which is a special case of HPC)  applied to dynamical systems such as  the logistic map in chaos theory. defined as X(k) = 4 X(k) (1 - X(k-1)). For all these systems, the loss of precision propagates exponentially, to the point that after 50 iterations, all generated values are completely wrong. Tons of articles have been written on this subject - none of them acknowledging the faulty…See More
Tuesday
Vincent Granville posted a blog post

Great Saturday Reading

Here is our selection of featured articles and resources posted in the last few days:New Machine Learning Competition, $2,000 Award Book: Complex Network Analysis in Python …See More
Nov 11
Vincent Granville posted blog posts
Nov 8

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

High Precision Computing in Python or R

Posted on November 13, 2017 at 7:00pm 0 Comments

Here we discuss an application of HPC (not high performance computing, instead high precision computing, which is a special case of HPC)  applied to dynamical systems such as  the logistic map in chaos theory. defined as X(k) = 4 X(k) (1 - X(k-1)). 

For all these systems, the loss of precision propagates exponentially, to the point that after 50 iterations, all generated values are completely wrong. Tons of articles have been written on this subject - none of them acknowledging the…

Continue

Great Saturday Reading

Posted on November 11, 2017 at 4:55pm 0 Comments

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

Continue

Beginners Guide to Chatbots

Posted on November 8, 2017 at 1:30pm 0 Comments

Summary:  This is the first in a series about Chatbots.  In this first installment we cover the basics including their brief technological history, uses, basic design choices, and where deep learning comes into play.  In subsequent articles we’ll describe in more detail about how they are actually programmed and best practice dos and don’ts.…

Continue

DSC Competition for Data Science and Quant Pros

Posted on November 8, 2017 at 12:00pm 0 Comments

Data Science Central (DSC) is excited to announce our competition to solve a new, interesting problem in statistical science, pertaining to stochastic processes. DSC members are invited and encouraged, to submit a theoretical solution or an application to real life problems, including but not limited to fintech, operations research, statistical science, computer science, economics, engineering, social, actuarial, biological or physical sciences.

The statistical process central to this…

Continue

Fascinating Time Series with Cool Applications

Posted on November 6, 2017 at 8:30pm 0 Comments

Here we describe well-known chaotic sequences, including new generalizations, with application to random number generation, highly non-linear auto-regressive models for times series, simulation, random permutations, and the use of big numbers (libraries available in programming languages to work with numbers with hundreds of decimals) as standard computer precision almost always produces completely erroneous results after a few iterations  -- a fact rarely if ever mentioned in the scientific…

Continue

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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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