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

What's the most advanced math you ever used in data science projects?

Started Mar 3 0 Replies

I have used quite a bit of advanced math, especially to solve problems in experimental mathematics using data science methods. For instance, solving stochastic integral equations. You can find the…Continue

One day, will humans be to AI what dogs are to humans now?

Started this discussion. Last reply by Vincent Granville Feb 28. 3 Replies

Do you think that one day, humans will find a way to not work and enjoy the life, relying on robots to help them with their needs, just like dogs who don't need to spend their time finding food and…Continue

Measuring Audience Overlap

Started this discussion. Last reply by Mercedes Feb 8. 3 Replies

Hi,I am looking for a tool (online app if possible) that measures the overlap in the number of users between two websites A and B, a tool that would offers statistics such asWebsite A had x visitors…Continue

Optimizing Office Furniture and Enterprise Real Estate Purchases

Started Jan 22 0 Replies

It is well know that office furniture / computer equipment, as well as renting / leasing or purchasing real estate to host your employees, is very expensive for corporations. Are there any companies…Continue

 

Vincent Granville's Page

Profile Information

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.
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/vincentg
Professional Status
C-Level
Years of Experience:
15
Your Company:
Data Science Central, AnalyticBridge
Industry:
Internet
Your Job Title:
Executive Data Scientist, Co-Founder
How did you find out about DataScienceCentral?
Tim Matteson
Interests:
Networking, New venture, Recruiting, Other
What is your Favorite Data Mining or Analytical Website?
http://www.datasciencecentral.com
What Other Analytical Website do you Recommend?
http://www.analyticbridge.com

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

Dumitru Puscasu liked Vincent Granville's blog post Fast Combinatorial Feature Selection with New Definition of Predictive Power
4 hours ago
Dr. Mohammed Khursheed Akhtar liked Vincent Granville's page Previous Digests
6 hours ago
John Lewis commented on Vincent Granville's blog post Fascinating New Results in the Theory of Randomness
"Whew!  This will definitely take several readings before I feel I have understool most of the ideas contained here. Thanks for posting it."
21 hours ago
John Lewis liked Vincent Granville's blog post Fascinating New Results in the Theory of Randomness
21 hours ago
Marc Cox liked Vincent Granville's blog post Fascinating New Results in the Theory of Randomness
yesterday
Tauheedul Ali liked Vincent Granville's blog post 33 Statistical Concepts Explained in Simple English - Part 10
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Vincent Granville's 2 blog posts were featured
yesterday
Vincent Granville posted a blog post

Data Science Central Weekly Digest, March 25

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
yesterday
Chris Barnes liked Vincent Granville's blog post Fascinating New Results in the Theory of Randomness
Sunday
Prasanth liked Vincent Granville's discussion SQL to NoSQL translator
Sunday
Akshay Milwani liked Vincent Granville's blog post The Fundamentals of Data Science
Saturday
Jean-Pierre Haddad liked Vincent Granville's blog post Fascinating New Results in the Theory of Randomness
Friday
Tauheedul Ali liked Vincent Granville's blog post Advanced Machine Learning with Basic Excel
Thursday
Vincent Granville posted a blog post

Data Science Central Thursday Digest, March 21

You will find here our selection of featured articles and resources posted since Monday. Resources and TutorialsFascinating New Results in the Theory of Randomness +Determining Sample Size in One Picture …See More
Thursday
Aida Benito liked Vincent Granville's blog post 40 Techniques Used by Data Scientists
Wednesday
Monami Mukherjee liked Vincent Granville's blog post Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics
Mar 17

Comment Wall (15 comments)

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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/

At 12:21pm on September 25, 2014, Christian Block said…

Hello Vincent, 

I just found DataScienceCentral and wanted to say thank you for putting it together! I'm looking forward to reading through more of the content and checking out your book (which I have ordered).  

Best Regards,

Christian Block

Vincent Granville's Videos

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Vincent Granville's Blog

Data Science Central Weekly Digest, March 25

Posted on March 24, 2019 at 10:00am 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

Data Science Central Thursday Digest, March 21

Posted on March 21, 2019 at 10:00am 0 Comments

You will find here our selection of featured articles and resources posted since Monday. 

Resources and Tutorials

Continue

Fascinating New Results in the Theory of Randomness

Posted on March 20, 2019 at 6:00pm 1 Comment

Updated on March 24. See new sections on Fibonacci numbers [3.2.(b)], comparing stochastic processes [4.1.(b)], connection with Brownian motions [4.1.(c)], new material in section 4.3, and new addition in the Appendix [5.4].

I present here some innovative results from my most recent research on stochastic processes. chaos modeling, and dynamical systems, with applications to Fintech, cryptography, number theory, and random number…

Continue

Data Science Central Weekly Digest, March 18

Posted on March 17, 2019 at 7:30am 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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