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Vincent Granville
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  • Issaquah, WA
  • United States
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Vincent Granville's Page

Latest Activity

Vincent Granville posted a discussion

Can Python do the following?

These were features that I liked in Perl. Wondering if there is a way to make it work with Python?Automated memory allocation / de-allocation (for variables, arrays, hash tables etc.)Turning your program into an executableAutomated variable initialization (variables, arrays don't even need to be declared, much less initialized)Automated type casting (e.g. automatically treating a same variable as an integer or string depending on the context: integer when performing a multiplication, or string…See More
1 hour ago
Vincent Granville's blog post was featured

Free Book: Applied Stochastic Processes

Full title: Applied Stochastic Processes, Chaos Modeling, and Probabilistic Properties of Numeration Systems. Published June 2, 2018. Author: Vincent Granville, PhD. (104 pages, 16 chapters.)This book is intended for professionals in data science, computer science, operations research, statistics, machine learning, big data, and mathematics. In 100 pages, it covers many new topics, offering a fresh perspective on the subject. It is accessible to practitioners with a two-year college-level…See More
Oct 3
Vincent Granville posted a blog post

Lots of Open Source Datasets to Make Your AI Better

Summary: There are several approaches to reducing the cost of training data for AI, one of which is to get it for free. Here are some excellent sources.Recently we wrote that training data (not just data in general) is the new oil. It’s the difficulty and expense of acquiring labeled training data that causes many deep learning projects to be abandoned.It also matters a great deal just how good you want your new deep learning app to be. A 2016 study by Goodfellow, Bengio and Courville concluded…See More
Oct 3
Vincent Granville posted a blog post

Introduction to Deep Learning

Guest blog post by Zied HY. Zied is Senior Data Scientist at Capgemini Consulting. He is specialized in building predictive models utilizing both traditional statistical methods (Generalized Linear Models, Mixed Effects Models, Ridge, Lasso, etc.) and modern machine learning techniques (XGBoost, Random Forests, Kernel Methods, neural networks, etc.). Zied run some workshops for university students (ESSEC, HEC, Ecole polytechnique) interested in Data Science and its applications, and he is the…See More
Sep 21

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

Lots of Open Source Datasets to Make Your AI Better

Posted on October 3, 2018 at 10:49am 0 Comments

Summary: There are several approaches to reducing the cost of training data for AI, one of which is to get it for free. Here are some excellent sources.

Recently we wrote that training data (not just data in general) is the new oil. It’s the difficulty and expense of acquiring labeled training data that causes many deep learning projects to be abandoned.

It also matters a great deal just how good you want your new deep learning app to be. A 2016 study by…

Continue

Introduction to Deep Learning

Posted on September 21, 2018 at 12:00pm 0 Comments

Guest blog post by Zied HY. Zied is Senior Data Scientist at Capgemini Consulting. He is specialized in building predictive models utilizing both traditional statistical methods (Generalized Linear Models, Mixed Effects Models, Ridge, Lasso, etc.) and modern machine learning techniques (XGBoost, Random Forests, Kernel Methods, neural networks, etc.). Zied run some workshops for university students (ESSEC, HEC, Ecole polytechnique) interested in Data…

Continue

Analytics Translator – The Most Important New Role in Analytics

Posted on September 12, 2018 at 5:30pm 0 Comments

Summary:  The role of Analytics Translator was recently identified by McKinsey as the most important new role in analytics, and a key factor in the failure of analytic programs when the role is absent.

 

The role of Analytics Translator was…

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New Perspective on the Central Limit Theorem and Statistical Testing

Posted on September 10, 2018 at 9:07pm 0 Comments

You won't learn this in textbooks, college classes, or data camps. Some of the material in this article is very advanced yet presented in simple English, with an Excel implementation for various statistical tests, and no arcane theory, jargon, or obscure theorems. It has a number of applications, in finance in particular. This article covers several topics under a unified approach, so it was not easy to find a title. In particular, we discuss:

  • When the central limit theorem…
Continue

Free Book: Applied Stochastic Processes

Posted on September 8, 2018 at 11:16am 0 Comments

Full title: Applied Stochastic Processes, Chaos Modeling, and Probabilistic Properties of Numeration Systems. Published June 2, 2018. Author: Vincent Granville, PhD. (104 pages, 16 chapters.)

This book is intended for professionals in data science, computer science, operations research, statistics, machine learning, big data, and mathematics. In 100 pages, it covers many new topics, offering a fresh perspective on the subject. It is accessible to…

Continue

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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