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

Data science workstation vs. cloud service provider or via on on-premises data center.

Started this discussion. Last reply by Vincent Granville Apr 13. 1 Reply

I wanted to get your thoughts on data science workstations? We’re seeing an uptick in product releases/messaging around DS workstations from several hardware vendors and I wanted to get your take on…Continue

How to deal with missing data

Started this discussion. Last reply by Prateek Baranwal Feb 6. 1 Reply

Originally posted by Vincent Ajayi. The most common challenge faced by data scientists (DS) and…Continue

Simulating Distributions with One-Line Formulas, even in Excel

Started this discussion. Last reply by Dennis Sweitzer Feb 7. 6 Replies

If you don't like using black-box R functions, or you don't have access to these functions, here are simple options to simulate deviates from various distributions. They can even be implemented in…Continue

Moments of Order Statistics

Started this discussion. Last reply by Prateek Baranwal Feb 6. 2 Replies

Continue

 

Vincent Granville's Page

Profile Information

Company:
Data Science Central, AnalyticBridge
Job Title:
Executive Data Scientist, Co-Founder
Seniority:
C-Level
Industry:
Internet
Short Bio:
Data science pioneer, founder, author, CEO, investor, 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), domains (data science, operations research, machine learning, computer science, business intelligence, statistics, applied mathematics, growth hacking, IoT) and roles (data scientist, founder, CFO, CEO, HR, product development, marketing, media buyer, operations, management consulting).

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, automated exploratory data analysis with data dictionaries, data videos as a visualization tool, automated data science, 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. He also holds a few patents on scoring technology, and raised $6 MM in VC funding for his first startup. 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 here and includes top publications, presentations, and work experience with Visa, Microsoft, eBay, NBC, Wells Fargo, and other organisations.

Follow me on Twitter at @AnalyticBridge.
LinkedIn Profile:
http://www.linkedin.com/in/vincentg
Interests:
Networking, New venture, Recruiting, Other

Bio

Data science pioneer, founder, author, CEO, investor, 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 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.

Latest Activity

Vincent Granville's blog post was featured

Introducing an All-purpose, Robust, Fast, Simple Non-linear Regression

The model-free, data-driven technique discussed here is so basic that it can easily be implemented in Excel, and we actually provide an Excel implementation. It is surprising that this technique does not pre-date standard linear regression, and is rarely if ever used by statisticians and data scientists. It is related to kriging and nearest neighbor interpolation, and apparently first mentioned in 1965 by Harvard scientists working on GIS (geographic information systems). It was referred back…See More
20 hours ago
Vincent Granville commented on Monika Wahi's blog post How do you know what independent variables to include in a regression model?
"If you use a robust regression models (like the one I designed, see here) then you can use all variables, even duplicate copies of the same variable (they won't have any impact on final results, and the multi-collinearity won't be an…"
Nov 15
Vincent Granville commented on Vincent Granville's blog post Interesting Application of the Poisson-Binomial Distribution
"Thank you Bryan for your insightful comment. "
Nov 15
Bryan M. Gorman commented on Vincent Granville's blog post Interesting Application of the Poisson-Binomial Distribution
"The Poisson Binomial distribution can be evaluated exactly in quadratic time (n^2) by convolving each of the n 2-point Bernoulli densities, or equivalently using generating functions. I use it to predict the outcome of k/n classifiers under…"
Nov 13
Frank Lombard replied to Vincent Granville's discussion One day, will humans be to AI what dogs are to humans now?
"The idea of silicon mimicking biological neurons isn't so straight forward as simply a challenge. Biological systems float in gilia and can move about to form connections. I don't know of any form of silicon technology that can do that. On…"
Nov 11
Vincent Granville's blog post was featured

Interesting Application of the Poisson-Binomial Distribution

While the Bernoulli and binomial distributions are among the first ones taught in any elementary statistical course, the Poisson-Binomial is rarely mentioned. It is however one of the simplest discrete distributions, with applications in survey analysis, see here. In this article, we are dealing with experimental…See More
Nov 10
Vincent Granville posted a blog post

Interesting Application of the Poisson-Binomial Distribution

While the Bernoulli and binomial distributions are among the first ones taught in any elementary statistical course, the Poisson-Binomial is rarely mentioned. It is however one of the simplest discrete distributions, with applications in survey analysis, see here. In this article, we are dealing with experimental…See More
Nov 10
Karen Skeen liked Vincent Granville's blog post New Books and Resources for DSC Members
Nov 8
Karen Skeen liked Vincent Granville's blog post Machine Learning and Data Science Cheat Sheet
Nov 8
Karen Skeen liked Vincent Granville's blog post Time series, Growth Modeling and Data Science Wizardy
Nov 8
Daren Scot Wilson liked Vincent Granville's blog post The Death of the Statistical Tests of Hypotheses
Oct 31
Vincent Granville's blog post was featured

Thursday News, October 29

Here is our selection of featured articles and technical resources posted since Monday:AnnouncementsFully online MS in Data Science at CUNYDSC ArticlesHow Kids Channel Their Internal Data Scientist to Become Candy Optimization Machines...…See More
Oct 29
Vincent Granville's blog post was featured

Weekly Digest, October 26

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  Featured Resources and Technical Contributions …See More
Oct 25
Federica Gazzelloni liked Vincent Granville's blog post My Best Data Science, Machine Learning and Math Related Articles
Oct 24
Federica Gazzelloni liked Vincent Granville's blog post Why Logistic Regression should be the last thing you learn when becoming a Data Scientist
Oct 24
Vincent Granville's blog post was featured

Thursday News, October 22

Here is our selection of featured articles and technical resources posted since Monday:AnnouncementLearn why 63% of firms will be advancing their adoption of AI by 2023.Technical ResourcesFree book - Cloud Native, Containers and Next-Gen Apps…See More
Oct 22

Comment Wall (16 comments)

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At 6:53pm on May 04, 2019, Florent Rudel Ndeffo gave Vincent Granville a gift
Gift
Thank you for the documentations. Priceless! :)
At 9:13am on December 13, 2018, victor zurkowski said…

Dear Vincent,

Do you know how long does membership approval in "Analytic Bridge" take? I want to submit an answer to the self-correcting random walk problem. The answer is long, and I left a copy of my document (not the final draft) in Github.

At 6:24am on October 01, 2017, Nitesh Choudhary gave Vincent Granville a gift
Gift
Your posts are very informative and I have learned a lot from them. Thanks for sharing!
At 1:37pm on June 23, 2016, Bill Bahl said…

Dr. Granville,

I enjoyed your white paper on Building Dashboards that Flow and could not agree more with minimalism. One thing that seems to be missing from the dashboard packages I've seen is control charts.  At least for the process owner, my personal opinion is a control chart should be the first chart.  If the process is not stable and predicable, statistical analysis seems futile.  Before I retired (two months ago) we started including these in the process owners' LEAN PIT boards.  We generated them in Minitab.  It only takes a few clicks once the data is paste into Minitab.  Bill Bahl

At 12:05pm on February 11, 2016, Dean Pangelinan said…

Dr. Granville,

Regarding the passerelle options for the Data Science certification program, does the notation of "IEEE Computer Science Society - Member" refer to Associate Membership in the IEEE Computer Society, or to full IEEE Membership with additional membership in the IEEE Computer Science Society?

Please advise, at your earliest convenience.

--  Dean Pangelinan

At 5:05pm on June 21, 2015, Sankara Kumaravel gave Vincent Granville a gift
Gift
Dear Dr.Vincent, Thanks for preserving such a nice professional web page for Data Analytics, this is really help for the novice like me.
At 5:28am on June 15, 2015, Lissy Able said…

Hi Vincent,

Can you suggest some points or links about serious data quality issue with the information pulled.

Thanks

Lissy

At 3:38pm on March 11, 2015, Donald Tynes said…

Vincent,

I recently was hired as a data scientist. As a new hire, leading the department of Business Intelligence, I am faced with self-posed questions such as, "What do I need to accomplish in the first 5 days?" And, "What should I accomplish in the first month?" And, of course, "How do I develop a long-term plan for transforming the business into a data-driven organization?" To make the problem of determining how I should focus my attention even more complicated, I have a single employee whom I want to groom to understand the algorithms that I am implementing. Also, I have a CEO who only agreed to hire for this position because the CIO, CFO, and COO encouraged him to do so, but he is highly skeptical of what data science can do for the organization; this complicates matters too because it puts on me a pressure to be dazzling right out-of-the-box. 

I have given these questions considerable thought. I am on day 3 of my new job. I have decided to orient myself on the business' data, query tools, and self-service tools, such as QlikView. I have so many ideas, I have difficulty in choosing a single direction in which I should run. I must note that I want to be significantly impactful while minimizing disruptions in the business' daily functions. To that end, I keep thinking, "run a clustering analysis! Discover the patterns and trends in the company's data to begin the model-building process."

What advice would you give a young data scientist on his 4th day on the job (as it is for me, tomorrow)? 

At 5:22am on December 3, 2014, Harvey Summers said…

I thought you might like this site: http://rpsychologist.com/d3/CI/ 

Interpreting Confidence Intervals

an interactive visualization

At 11:29pm on October 31, 2014, Philippe Van Impe said…

Being from Belgium, you are welcome to join our meetup group about data sciences http://www.meetup.com/Brussels-Data-Science-Community-Meetup/

Vincent Granville's Videos

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Vincent Granville's Blog

Introducing an All-purpose, Robust, Fast, Simple Non-linear Regression

Posted on November 23, 2020 at 6:00pm 0 Comments

The model-free, data-driven technique discussed here is so basic that it can easily be implemented in Excel, and we actually provide an Excel implementation. It is surprising that this technique does not pre-date standard linear regression, and is rarely if ever used by statisticians and data scientists. It is related to kriging and nearest neighbor interpolation, and apparently first mentioned in 1965 by Harvard scientists working on GIS (geographic information systems). It was referred…

Continue

Interesting Application of the Poisson-Binomial Distribution

Posted on November 10, 2020 at 6:30pm 2 Comments

While the Bernoulli and binomial distributions are among the first ones taught in any elementary statistical course, the Poisson-Binomial is rarely mentioned. It is however one of the simplest discrete distributions, with applications in survey analysis, see here. In this article, we are dealing with…

Continue

Thursday News, October 29

Posted on October 29, 2020 at 9:00am 0 Comments

Here is our selection of featured articles and technical resources posted since Monday:

Announcements

DSC Articles

Continue

Weekly Digest, October 26

Posted on October 25, 2020 at 12:00pm 0 Comments

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  

Featured Resources and Technical…

Continue
 
 
 

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