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

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

Can AI Robots Beat Professional Stock Traders?

Started May 21 0 Replies

I am not talking here about high frequency trading, which has been done by automated algorithms long ago, and that humans can not beat (if done well!) But more like, if you allow a robot or a human…Continue

Which Data Science Techniques Should I Introduce to my Team Members?

Started this discussion. Last reply by Yann MAINVIS May 17. 1 Reply

This is an interesting question asked by a director managing a team of scientists, who wants to keep his team updated on data science techniques. Below is the email exchange in question:Hey Vincent.…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

ANISH XAVIER liked Vincent Granville's blog post Data Science Cheat Sheet
2 hours ago
Vincent Granville posted a blog post

Weekly Digest, June 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.Featured Resources and Technical ContributionsMultivariate Regression with Neural Networks - Unique, Exact and Generic Models…See More
2 hours ago
Shyam Sundar Shankar liked Vincent Granville's discussion An Excel Tutorial on Analyzing Large Data Sets
16 hours ago
Shyam Sundar Shankar liked Vincent Granville's group Tutorials
16 hours ago
Vincent Granville commented on Vincent Granville's blog post Simple Solution to Feature Selection Problems
"You are correct Steen. I updated and re-loaded the spreadsheet. It does not change the conclusions however, because all the information to compute column D is in column B, and all the information to compute column E is in column C. "
20 hours ago
Shiv Shankar liked Vincent Granville's blog post Learn Python in 3 days : Step by Step Guide
yesterday
Steen Nielsen commented on Vincent Granville's blog post Simple Solution to Feature Selection Problems
"Dear Vincent! Is there not something wrong with your spreadsheet model? You are writing correl (AD) but infact your correlation is between A and B? best regards Steen "
yesterday
victor zurkowski commented on Vincent Granville's blog post Two Beautiful Mathematical Results
"It is worth mentioning that the identity $\Sigma_{k=0}{\infty} x^{3k} = \frac{1}{1-x^3}$ and the term by term integration hold for $x \in (0,1)$. To justify the evaluation of the series at $ x= - 1$ still equals the value of the integral, one…"
yesterday
Dale Swinford liked Vincent Granville's blog post Spectral Clustering – How Math is Redefining Decision Making
Friday
Gerardo Rojas liked Vincent Granville's blog post Simple Solution to Feature Selection Problems
Thursday
Vincent Granville posted blog posts
Thursday
Prabhakaran Sampath liked Vincent Granville's blog post Simple Solution to Feature Selection Problems
Thursday
Edgar Isusquiza commented on Vincent Granville's blog post First Doctorship in Data Science
"Dear Vincent, I'm interested about the details and how to apply."
Thursday
Daniel Reimann liked Vincent Granville's discussion Using AI to Write Articles and Research Papers
Thursday
Rajendra Timilsina, Ph. D. liked Vincent Granville's blog post 24 Uses of Statistical Modeling (Part I)
Thursday
Vincent Granville posted blog posts
Wednesday

Comment Wall (14 comments)

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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

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

Weekly Digest, June 25

Posted on June 24, 2018 at 3:00am 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.

Featured Resources and Technical Contributions

Continue

Will the job outlook for data scientists severely decline after 2020?

Posted on June 21, 2018 at 12:30pm 0 Comments

Interested question posted on Quora recently. Here is my take on this.

Just put the next buzz word on your resume when you graduate, maybe AI engineer? I completed my PhD in computational statistics 25 years ago. It was in fact data science (image remote sensing), but under a different name. I changed my job title from statistician to data scientist many years ago, and I may dot it again if needed. There is more and more data to process, so the need will grow, but it will grow very…

Continue

Simple Solution to Feature Selection Problems

Posted on June 20, 2018 at 5:00am 2 Comments

We discuss a new approach for selecting features from a large set of features, in an unsupervised machine learning framework. In supervised learning such as linear regression or supervised clustering, it is possible to test the predicting power of a set of features (also called independent variables by statisticians, or predictors) using metrics such as goodness of fit with the response (the dependent variable), for instance using the R-squared coefficient. This makes the process of feature…

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