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

Are data science or stats curricula in US too specialized?

Started this discussion. Last reply by Vincent Granville Sep 12. 2 Replies

I earned my education in Belgium and never attended college in US, so it is hard for me to answer this question, even though all my professional experience and career took place in US. Yet sometimes…Continue

Analytic-related domain names for sale

Started Aug 11 0 Replies

I have a few domain names that I haven't used in years, on Network Solutions. I've tried to find their valuation using a Godaddy tool (they use a data science algorithm, supposedly!) and here is my…Continue

Using AI to Write Articles and Research Papers

Started Jun 17 0 Replies

I am wondering if news outlets sometimes use bots to write articles. I've seen in the past articles that looked like they were written by a bot. The sentences didn't make much sense, and it almost…Continue

Will GDPR kill business in Ireland?

Started this discussion. Last reply by James Theobald Jun 7. 2 Replies

Companies such as Facebook and Apple use Ireland as a tax shelter, with great benefits for them. As billion of dollars in lawsuits could result from GDPR, will Ireland still be able to attract big…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

Dr. Bruno Louis liked Vincent Granville's blog post Statistical Significance and p-Values Take Another Blow
8 hours ago
Dan K. Hansen liked Vincent Granville's blog post Statistical Significance and p-Values Take Another Blow
10 hours ago
Sameer Verma liked Vincent Granville's blog post 13 Great Blogs Posted in the last 12 Months
11 hours ago
Paul Bremner commented on Vincent Granville's blog post Statistical Significance and p-Values Take Another Blow
"I couldn't agree more with what you say, particularly in highlighting the poor review process at journals and the incentives to publish something "different." I think particularly in the medical field the view amongst doctors is that…"
22 hours ago
Vincent Granville posted a blog post

Statistical Significance and p-Values Take Another Blow

I read an article this morning, about a top Cornell food researcher having 13 studies retracted, see here. It prompted me to write this blog. It is about data science charlatans and unethical researchers in the Academia, destroying the value of p-values again, using a well known trick called p-hacking, to get published in top journals and…See More
23 hours ago
João Pires liked Vincent Granville's blog post Introduction to Deep Learning
yesterday
Jawad OUBAHA liked Vincent Granville's blog post Introduction to Deep Learning
yesterday
David Reinke commented on Vincent Granville's blog post Introduction to Deep Learning
"Good post. I also recommend the book Deep Learning by Ian Goodfellow et al. MIT Press provides this as an open access online book: https://mitpress.mit.edu/books/deep-learning"
Thursday
Vincent Granville posted blog posts
Thursday
Ruhil Dongol liked Vincent Granville's blog post Introduction to Deep Learning
Thursday
Enkeleda Bocaj liked Vincent Granville's blog post Introduction to Deep Learning
Thursday
RASHMI liked Vincent Granville's blog post New Perspective on the Central Limit Theorem and Statistical Testing
Wednesday
RASHMI liked Vincent Granville's blog post Invitation to Join Data Science Central
Wednesday
Vincent Granville's blog post was featured

Invitation to Join Data Science Central

Join the largest community of machine learning (ML), deep learning, AI, data science, business analytics, BI, operations research, mathematical and statistical professionals: Sign up here. If instead, you are only interested in receiving our newsletter, you can subscribe here. There is no cost.…See More
Monday
Stephan O'Bryan liked Vincent Granville's blog post Data Science Cheat Sheet
Monday
Ramahuma John commented on Vincent Granville's blog post Free Book: Applied Stochastic Processes
"Thank you"
Monday

Comment Wall (14 comments)

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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/

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

At 6:19am on August 5, 2014, Nasir M. Uddin, Ph.D. said…

Hi Vincent:

This is a great platform to be informed with any latest updates in the field of data science - thank you so much for such a platform.

Regards, Nasir 

Vincent Granville's Videos

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Vincent Granville's Blog

Statistical Significance and p-Values Take Another Blow

Posted on September 21, 2018 at 2:00pm 1 Comment

I read an article this morning, about a top Cornell food researcher having 13 studies retracted, see here. It prompted me to write this blog. It is about data science charlatans and unethical researchers in the Academia, destroying the value of p-values again, using a well known trick called p-hacking, to get published…

Continue

Thursday News: Deep Learning, Stats Book, AI, MLasS Comparison, Feature Selection (Overview)

Posted on September 20, 2018 at 11:00am 0 Comments

Here is our selection of featured resources and articles posted this week:

Resources

Continue

Introduction to Deep Learning

Posted on September 19, 2018 at 1:00pm 1 Comment

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.).…

Continue

Weekly Digest, September 17

Posted on September 16, 2018 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.

Announcement

  • Enterprise AI: Take the Plunge. Data science and advanced analytics front-runner Dataiku announces the release of…
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