Subscribe to DSC Newsletter
Vincent Granville
  • Male
  • Issaquah, WA
  • United States
Share

Vincent Granville's Friends

  • George F. Hart
  • Charles Fox
  • Antoine Bruyns
  • Tahir Irshad Siddiqi
  • Tullio Siragusa
  • Manu Dixit
  • john
  • Gautam Ganesh
  • Dilip MS
  • Eelco van Gelderen
  • Linh Tran
  • Crispin Stromberg
  • Paul Robert Bolton II
  • Rosaria Silipo
  • Matthew Holgate

Vincent Granville's Discussions

Data Science Content Not Found on Google

Started May 15 0 Replies

Here is some great content that you won't find on Google. I hope to add more in the future, and feel free to email me at vincentg@datashaping.com if you want to add some of your links.…Continue

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

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 @AnalyticBridge.
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
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

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

Vincent Granville's 2 blog posts were featured
1 hour ago
Dan K. Hansen liked Vincent Granville's page Data Science Book
2 hours ago
Sonia Martinez liked Vincent Granville's blog post Data Science & Machine Learning Encyclopedia - 4,000 Entries
2 hours ago
Naresh Nelaturi liked Vincent Granville's blog post Data Science & Machine Learning Encyclopedia - 4,000 Entries
8 hours ago
Naresh Nelaturi liked Vincent Granville's discussion Top 10 Machine Learning Algorithms
8 hours ago
Jansen Davis liked Vincent Granville's blog post Hitchhiker's Guide to Data Science, Machine Learning, R, Python
14 hours ago
Michael Clayton commented on Vincent Granville's blog post The Death of the Statistical Tests of Hypotheses
"Thanks...again.   The key seems to be visualization first then structured statements that meet legal requirements in court appearances, and academic communications standards.  For example. I was once told by a legal eagle that any…"
17 hours ago
Alfred liked Vincent Granville's blog post 10 types of regressions. Which one to use?
23 hours ago
Alfred liked Vincent Granville's blog post The Death of the Statistical Tests of Hypotheses
23 hours ago
James Chang liked Vincent Granville's blog post Hitchhiker's Guide to Data Science, Machine Learning, R, Python
yesterday
James Chang liked Vincent Granville's blog post Hitchhiker's Guide to Data Science, Machine Learning, R, Python
yesterday
Stéphane liked Vincent Granville's blog post 21 data science systems used by Amazon to operate its business
yesterday
Shafiq Ahamed Mohamed Ali liked Vincent Granville's blog post Hitchhiker's Guide to Data Science, Machine Learning, R, Python
Monday
Reuben Kim Hine commented on Vincent Granville's blog post Top 10 Hot Data Science Technologies
"Hello Vincent, In regards to: Adapting modern predictive algorithms to a distributed architecture, are you including Hadoop? I am waiting on a $269 laptop with I5 cpu and 8 gb of ram, which I plan to build Hadoop. I am certainly not the most…"
Monday
Sione Palu commented on Vincent Granville's blog post Deep Learning: Definition, Resources, Comparison with Machine Learning
"Quote :  "still rely on relatively old-fashioned techniques". Some are quite new. One example is the deep non-negative matrix factorization (NMF): "A Deep Semi-NMF Model for Learning Hidden…"
Sunday
Siying Liu liked Vincent Granville's discussion Our Data Science Apprenticeship is Now Live
Sunday

Comment Wall (13 comments)

You need to be a member of Data Science Central to add comments!

Join Data Science Central

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
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

  • Add Videos
  • View All

Vincent Granville's Blog

Data Science & Machine Learning Encyclopedia - 4,000 Entries

Posted on May 23, 2016 at 2:10pm 0 Comments

This is one of the first comprehensive machine learning, data science, statistical science, and computer science repository -- featuring many brand new scalable, big-data algorithms published in the last two years, such as automated cataloging, causation detection, or model-free tests of hypotheses, in addition to the classics. The original title for this project was Handbook of Data Science, but over time, it grew much bigger than an handbook. This is still an ongoing…

Continue

Hitchhiker's Guide to Data Science, Machine Learning, R, Python

Posted on May 20, 2016 at 11:30am 0 Comments

Thousands of articles and tutorials have been written about data science and machine learning. Hundreds of books, courses and conferences are available. You could spend months just figuring out what to do to get started, even to understand what data science is about.

In this short contribution, I share what I believe to be the most valuable resources - a small list of top resources and starting points. This will be most valuable to any data practitioner who has very little free…

Continue

Weekly Digest, May 23

Posted on May 18, 2016 at 9:30am 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

10 Great Data Science Articles by Bernard Marr

Posted on May 16, 2016 at 11:02am 0 Comments

Bernard Marr is a best-selling business author, keynote speaker and consultant in big data, analytics and enterprise performance. As the founder and CEO of the Advanced Performance Institute he is one of the world's most highly respected thought leaders anywhere when it comes to data in business. He regularly advises companies and government organisations on how to improve their performance and gain better insights from their data. …

Continue
 
 
 

Follow Us

Videos

  • Add Videos
  • View All

Resources

© 2016   Data Science Central   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service