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

10 Most Commented DSC Articles

Started Mar 30 0 Replies

Sometimes you read an article because it is very interesting, and relevant to your job. Sometimes, you find a lot of value in the comments posted by peers, even much more than in the article itself.…Continue

10 Popular Forum Questions and Discussions on DSC

Started Mar 29 0 Replies

These are selected forum questions and discussions, some of them very recent, some with many comments - all of them being quite popular. We invite you to add your comments, or to ask your own…Continue

Tough Math Question about Correlations

Started Mar 21 0 Replies

We all know that correlations range from - 1 to +1. What about correlations between random variables taking only on positive values, possibly from a Poisson, Exponential or Gamma joint distribution?…Continue

Gifts Received (3)

 

Vincent Granville's Page

Profile Information

Short Bio
Well rounded, visionary data science executive 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 @ROIdoctor.
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/vincentg
Field of Expertise
Analytics, Big Data, Data Science
Professional Status
C-Level
Years of Experience:
15
Your Company:
Data Science Central, AnalyticBridge
Industry:
Internet
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

Well rounded, visionary data scientist 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

Life Skipper commented on Vincent Granville's blog post When Does Deep Learning Work Better Than SVMs or Random Forests?
"Thanks for the article that led me all the way to the repository of the book,where many examples are presented in python (jupiter)notebooks. I especially liked the drawings that explain schematically each method.:):) I think it will be included in…"
23 minutes ago
Life Skipper liked Vincent Granville's blog post When Does Deep Learning Work Better Than SVMs or Random Forests?
33 minutes ago
John Sobiranski liked Vincent Granville's blog post Deep Learning Demystified
4 hours ago
Vincent Granville's blog post was featured

Deep Learning Demystified

Guest blog post by Christopher Dole and other contributors, originally posted here. Created by SoothSayerAnalytics. Deep Learning is one of the most revolutionary and disruptive technologies ever developed in Data Science.  Essentially, this is a class of…See More
5 hours ago
Vincent Granville posted a blog post

Deep Learning Demystified

Guest blog post by Christopher Dole and other contributors, originally posted here. Created by SoothSayerAnalytics. Deep Learning is one of the most revolutionary and disruptive technologies ever developed in Data Science.  Essentially, this is a class of…See More
5 hours ago
Rami Younes liked Vincent Granville's blog post 24 Uses of Statistical Modeling (Part I)
15 hours ago
Rami Younes liked Vincent Granville's blog post 24 Uses of Statistical Modeling (Part II)
15 hours ago
Simon Thompson commented on Vincent Granville's blog post When Does Deep Learning Work Better Than SVMs or Random Forests?
"Sebastian - for a lot of problems "it just works" isn't good enough, hence decision trees and rule mining. I think that at least some insight as to why a particular problem fits a opaque method is needed if you're not to come a…"
17 hours ago
Alfred liked Vincent Granville's blog post 43 New External Machine Learning Resources and Updated Articles
21 hours ago
Vincent Granville posted a blog post

Weekly Digest, May 2

Starred articles are new additions posted between Thursday and Sunday, published in the Monday edition exclusively. The Monday edition has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content. The Thursday edition covers articles…See More
yesterday
Mostofa Sarkar replied to Vincent Granville's discussion Our Data Science Apprenticeship is Now Live in the group Data Science Apprenticeship
"Hi Dr. Granville, I am interested. Please assess my profile and let me know. https://ca.linkedin.com/in/mostofa-sarkar-5382382b Regards Mostofa Sarkar"
yesterday
Vincent Granville's blog post was featured

When Does Deep Learning Work Better Than SVMs or Random Forests?

Guest blog by Sebastian Raschka, originally posted here.  If we tackle a supervised learning problem, my advice is to start with the simplest hypothesis space first. I.e., try a linear model such as logistic regression. If this doesn't work "well" (i.e., it doesn't meet our expectation or…See More
yesterday
®γσ, Lian Hu ENG liked Vincent Granville's blog post 11 Deep Learning Articles, Tutorials and Resources
yesterday
Steven Gray commented on Vincent Granville's blog post Learning R in Seven Simple Steps
"Great Article. A lot of great links. I am new to R-Programming and have found value in the links so far. This will be great for reference later as I learn more. "
yesterday
Steven Gray liked Vincent Granville's blog post Learning R in Seven Simple Steps
yesterday
Alfred liked Vincent Granville's blog post Black-box Confidence Intervals: Excel and Perl Implementation
yesterday

Comment Wall (13 comments)

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At 1:29pm on March 8, 2016, Alessia Talarico said…

Hello Vincent!

I hope that this email finds you well. I promise this is not spam!

My name is Alessia Talarico. I am a Research Assistant for Dr. Emmanuelle Vaast, a professor of Information Systems at the Desautels Faculty of Management and we have been studying the emergence of data scientists as an important new occupation.

Given your involvement in Data Science Central, you are an expert very well suited in the field of data science and data scientists.

Would it be possible for the two of us to have a short, Skype or phone based, interview, to discuss data scientists as a new type of job or occupation? Our interview would be for academic research purposes, would not last more than 15 minutes of your time, and would be scheduled at your convenience.

Please let me know if you have any question and do not hesitate to contact me via email (alessia.talarico@mail.mcgill.ca).

Looking forward to hearing from you.

 

Kind regards,

Alessia

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 

At 8:03am on January 8, 2013, Marc Jape said…
Vincent:

This is a great platform that I was not aware of. Keep up the good work.

Regards,
Marc

Vincent Granville's Videos

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Vincent Granville's Blog

Deep Learning Demystified

Posted on April 28, 2016 at 7:30pm 0 Comments

Guest blog post by Christopher Dole and other contributors, originally posted here. Created by SoothSayerAnalytics. 

Deep Learning is one of the most revolutionary and disruptive technologies ever developed in Data Science.  Essentially, this is…

Continue

Weekly Digest, May 2

Posted on April 27, 2016 at 3:30pm 0 Comments

Starred articles are new additions posted between Thursday and Sunday, published in the Monday edition exclusively. The Monday edition has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content. The Thursday edition covers articles…

Continue

When Does Deep Learning Work Better Than SVMs or Random Forests?

Posted on April 25, 2016 at 8:30pm 2 Comments

Guest blog by Sebastian Raschka, originally posted here.  

If we tackle a supervised learning problem, my advice is to start with the simplest hypothesis space first. I.e., try a linear model such as logistic regression. If this doesn't work "well" (i.e., it doesn't meet…

Continue

Learning R in Seven Simple Steps

Posted on April 22, 2016 at 8:00am 1 Comment

Guest blog post by Martijn Theuwissen, co-founder at DataCamp. Other R resources can be found here, and R Source code for various problems can be found here. A data science cheat sheet can be found…

Continue
 
 
 

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