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

Moments of Order Statistics

Started this discussion. Last reply by Vincent Granville May 24. 1 Reply

Continue

Question about the big O notation

Started this discussion. Last reply by Daren Scot Wilson May 27. 6 Replies

We all know that exponential functions grow faster than polynomials. Let us consider the following function: f(n) = n^a ⋅ (log n)^b ⋅ (log log n)^c ⋅ (log log log n)^d⋯ where the leading coefficient…Continue

Correlation between two sequences of irrational numbers

Started this discussion. Last reply by Vincent Granville May 4. 1 Reply

Let us consider the sequence x(n+1) = { b + x(n) } with x(0) = 0. Here the brackets represent the fractional part function. Thus x(n)= { nb } is related to Beatty sequences. If b is irrational, it is…Continue

What was your most difficult job interview question?

Started this discussion. Last reply by Johnothan Rears May 1. 2 Replies

Whether as a job applicant for a data science role, or as a hiring manager. Was it a technical question (mathematics, statistics, or coding problem?) What it a riddle? Or a general question? Were you…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

Tricia Aanderud liked Vincent Granville's blog post Weekly Digest, September 16
4 hours ago
Baharuddin Baharuddin liked Vincent Granville's blog post Two New Deep Conjectures in Probabilistic Number Theory
9 hours ago
Vincent Granville commented on Shahram Abyari's blog post Introduction to Outlier Detection Methods
"Hi John, I checked and I am also experiencing issues with the links. It used to work when initially posted. Anyway, I did some editing and removed the links in question."
18 hours ago
Bill C White liked Vincent Granville's blog post Six Degrees of Separation Between Any Two Data Sets
Monday
Sumudu Tennakoon liked Vincent Granville's blog post Blockchain and Artificial Intelligence
Monday
Vincent Granville liked Jorge Castanon's blog post 10 Machine Learning Methods that Every Data Scientist Should Know
Saturday
Vincent Granville liked Jorge Castanon's blog post 10 Visualizations Every Data Scientist Should Know
Saturday
Vincent Granville's blog post was featured

Weekly Digest, September 16

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.  AnnouncementBuilding Intelligent Apps with MongoDB and Google Cloud -…See More
Saturday
ajit jaokar liked Vincent Granville's blog post Two New Deep Conjectures in Probabilistic Number Theory
Saturday
ajit jaokar liked Vincent Granville's blog post Fascinating New Results in the Theory of Randomness
Saturday
Eduardo Area Sacristan liked Vincent Granville's blog post 140 Machine Learning Formulas
Saturday
Vincent Granville posted a blog post

Thursday News, September 12

This is our selection of featured articles and resources posted since Monday:AnnouncementMigrating R Applications to the Cloud - Upcoming WebinarTechnical ContributionsThe First Article About Theoretical Data Science (and easy to read)…See More
Sep 12
Ali Awadh liked Vincent Granville's blog post Misuses of Statistics: Examples and Solutions
Sep 11
Mehmet Gökce liked Vincent Granville's blog post 22 tips for better data science
Sep 11
Nate Whitten commented on Vincent Granville's blog post Six Degrees of Separation Between Any Two Data Sets
"Vincent, this is a great little experiment! Something interesting is that the pairwise correlations (as one would expect for synthetic correlations of 0.8) are dropping by roughly 0.2 at each step. With greater numbers of steps, the relationship…"
Sep 9
Jon-David Woods liked Vincent Granville's blog post Six Degrees of Separation Between Any Two Data Sets
Sep 9

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

Introduction to Authorship Analysis as a Text Classification/Clustering Problem

Posted on September 18, 2019 at 3:02pm 0 Comments

Guest blog post by Nabanita Roy.

Introduction:

The art and science of discriminating between writing styles of authors by identifying the characteristics of the persona of the authors and examining articles authored by them is called Authorship Analysis. It aims to determine characteristics of an individual like age, gender, native language and personality traits…

Continue

Introduction to Authorship Analysis as a Text Classification/Clustering Problem

Posted on September 18, 2019 at 3:02pm 0 Comments

Guest blog post by Nabanita Roy.

Introduction:

The art and science of discriminating between writing styles of authors by identifying the characteristics of the persona of the authors and examining articles authored by them is called Authorship Analysis. It aims to determine characteristics of an individual like age, gender, native language and personality traits…

Continue

Weekly Digest, September 16

Posted on September 14, 2019 at 8:30am 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.  

Announcement

  • Building…
Continue

Thursday News, September 12

Posted on September 12, 2019 at 10:30am 0 Comments

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

Announcement

Technical Contributions

Continue
 
 
 

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