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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 yesterday. 1 Reply

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Question about the big O notation

Started this discussion. Last reply by Vincent Granville yesterday. 1 Reply

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

Vincent Granville posted a blog post

Data Science Central Monday Digest, May 27

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
1 hour ago
Benny Tang liked Vincent Granville's blog post Free Deep Learning Textbook
yesterday
Vincent Granville replied to Vincent Granville's discussion Question about the big O notation
"Some readers noticed that you can't have an infinite sequence of embedded logarithms. Instead we could use the absolute value of the logarithm:  | log n |, | log log n ||, | log log log n ||| and so on. But then these are other issues.…"
yesterday
Vincent Granville replied to Smule Singer's discussion Recommendation system evaluation
"It is done using cross-validation if you have a training set. If you don't, you could test your system on simulated data or external data that contains a pre-computed / pre-tested recommendation field. If this is not possible, see here and…"
yesterday
Vincent Granville replied to Vincent Granville's discussion Moments of Order Statistics
"Here is an interesting summary table, featuring the order of magnitude for the range (source: see here):"
yesterday
Vincent Granville posted a blog post

Data Science Central Thursday Digest, May 23

Here is our selection of featured articles, resources and forum questions posted since Monday:Technical ResourcesFree Book: Foundations of Data Science (from Microsoft Research Lab) Deep Learning Explainability: Hints from Physics …See More
Thursday
Vincent Granville's 2 discussions were featured
Thursday
Mukund Ranjan liked Vincent Granville's blog post Free Book: Classification and Regression In a Weekend
Thursday
Mukund Ranjan liked Vincent Granville's blog post 29 Statistical Concepts Explained in Simple English - Part 13
Thursday
Rama P Kotipatruni liked Vincent Granville's blog post 29 Statistical Concepts Explained in Simple English - Part 13
Wednesday
Vincent Granville's blog post was featured

29 Statistical Concepts Explained in Simple English - Part 13

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on DSC.…See More
Wednesday
Vincent Granville commented on Vincent Granville's blog post A Beautiful Result in Probability Theory
"Joe Blitzstein pointed out (see here) that my theorem is a particular case of a general result that applies to exponential distributions, known as the Renyi representation. This general result is illustrated in the picture below and in…"
May 19
Vincent Granville's 2 blog posts were featured
May 19
Robert R. Tucci commented on Vincent Granville's blog post 7 Great Articles About TensorFlow
"If you are interested in the intersection of Tensorflow and quantum computing, you might be interested in my software  https://qbnets.wordpress.com/2019/05/14/qubiter-now-has-a-native-tensorflow-backend/"
May 19
Ribamar Matias liked Vincent Granville's blog post Free Book: Classification and Regression In a Weekend
May 19
Riccardo Cannaviello liked Vincent Granville's blog post Hitchhiker's Guide to Data Science, Machine Learning, R, Python
May 18

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
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/

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Vincent Granville's Blog

Data Science Central Monday Digest, May 27

Posted on May 26, 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.  

Featured Resources and Technical…

Continue

Data Science Central Thursday Digest, May 23

Posted on May 23, 2019 at 10:30am 0 Comments

Here is our selection of featured articles, resources and forum questions posted since Monday:

Technical Resources

Continue

29 Statistical Concepts Explained in Simple English - Part 13

Posted on May 21, 2019 at 5:30pm 0 Comments

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

Continue

Data Science Central Monday Digest, May 20

Posted on May 19, 2019 at 3:00pm 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.  

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