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

Do VC's Help Create or Destroy Innovation?

Started on Thursday 0 Replies

The answer is not black and white, but here are some of my thoughts:It is very difficult to beat VC-funded companies competing with you, even if you have a better mouse trap. They don't care if they…Continue

Looking for a search engine useful for professional data scientists

Started this discussion. Last reply by Lance Norskog yesterday. 1 Reply

I can barely find anything valuable on Google anymore, it looks like most of search result pages display either stuff for beginners, like high school students, or a few technical very advanced papers…Continue

New Mathematical Conjecture?

Started this discussion. Last reply by Vincent Granville Nov 2. 1 Reply

I thought the following fact was trivial, but could not find a proof anywhere. The proportion of integers with an odd number of distinct prime factors seems to be 1/2 as you would expect, but it…Continue

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

 

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

29 Statistical Concepts Explained in Simple English - Part 3

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
12 hours ago
Vincent Granville replied to Abel Fischer's discussion From academia to data science in healthcare: Is the learning path any different?
"My experience is opposite. Not that I am looking for a job in Academia, but more and more, I am doing academic-level research in theoretical & applied math, on my own, that involves a lot of data science in a setting very similar to…"
15 hours ago
Partha Pritam Deka liked Vincent Granville's blog post Invitation to Join Data Science Central
23 hours ago
Lance Norskog replied to Vincent Granville's discussion Looking for a search engine useful for professional data scientists
"Google Groups for particular communities are helpful, but, yeah the StackExchange ecosystem is turning out to be the best resource."
yesterday
Vincent Granville replied to Rafael Knuth's discussion What Is A Viable Use Case For Excel, And What Is Not?
"While Excel is the tool that I use most, I am wondering why it is so slow when processing (say) one million rows. I use to code in Perl (and its ancestors, like C, which share the same DNA) but there are unexpected benefits about Excel that few…"
yesterday
Pouya Esmailian liked Vincent Granville's discussion Do VC's Help Create or Destroy Innovation?
yesterday
Cumali Türkmenoğlu liked Vincent Granville's blog post Opinion: Is a PhD helpful for a data science career?
yesterday
Parmod Kumar liked Vincent Granville's blog post Free Deep Learning Book (MIT Press)
Monday
Vincent Granville posted a blog post

Weekly Digest, November 12

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.AnnouncementsJump-start your career as a data scientist, data engineer, or analytics manager in…See More
Sunday
Patrick J. Hagan liked Vincent Granville's blog post The Mathematics of Machine Learning
Sunday
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
Saturday
Rafael Knuth liked Vincent Granville's blog post Six categories of Data Scientists
Saturday
Vinod Sharma liked Vincent Granville's blog post Invitation to Join Data Science Central
Saturday
Laura Wyss commented on Vincent Granville's blog post Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics
"Well explained! I agree with all of these points. Thanks for sharing. If you want more info related this post visit here: https://www.windsor.ai/"
Saturday
Zhiyuan Qin liked Vincent Granville's discussion Looking for a search engine useful for professional data scientists
Friday
Costas Bouyioukos liked Vincent Granville's blog post Big data sets available for free
Friday

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

29 Statistical Concepts Explained in Simple English - Part 3

Posted on November 13, 2018 at 7:30pm 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

Weekly Digest, November 12

Posted on November 11, 2018 at 6:30am 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.

Announcements

  • Jump-start your career as a data scientist, data engineer, or analytics manager in…
Continue

Thursday News: AI, Data Scientists Survey, Case Studies, Do you need a PhD, Impact of VC's

Posted on November 8, 2018 at 12:30pm 0 Comments

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

Resources

Continue

Opinion: Is a PhD helpful for a data science career?

Posted on November 4, 2018 at 11:30am 1 Comment

The answer to this question is not black and white, and also depends on where you live, what you did during your PhD program, how much time and money you spent on it, what kind of jobs you are interested in, and what other experience you have. You could say the same thing about earning an MBA instead.

If your PhD took place abroad as in my case, you may have not spent much money to earn it (you might even have been well paid.) Depending on your school, it might have been…

Continue
 
 
 

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