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

Help needed to prove that Earth is not flat

Started this discussion. Last reply by Vincent Granville 8 hours ago. 13 Replies

Can someone show what the trajectory of an object falling on a "pancake-shape" Earth would be, according to the gravitation law? Also if Earth is flat but not infinite, it must have edges. Since…Continue

What tools can make data scientists more productive?

Started this discussion. Last reply by Rich Galan Mar 22. 1 Reply

What do you think? Below is my answer.Using tools that your competitors are not using, or developing ad-hoc solutions, and mastering them, is more important than the tool itself. Home-made solutions…Continue

Question for Actuaries: New Insurance Products (Pricing, Exclusions)

Started this discussion. Last reply by mark kertzner Mar 8. 1 Reply

I came up with a few ideas to either create new insurance companies, or better, for existing insurance companies to sell new products. I am wondering if any of the following already exists, and if…Continue

Correlation Coefficient in Flat Line Model

Started Feb 21 0 Replies

Let say that your model is Y = a + bX, (for instance X is the time) but you know that b = 0. In short, you are trying to get the best fit for Y = a. Of course a is your average computed on your…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
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

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

Derek Christensen liked Vincent Granville's discussion An Easier Way To Find R Documentation
51 minutes ago
Vincent Granville replied to Vincent Granville's discussion Help needed to prove that Earth is not flat
"Jim, exactly. I would imagine (but I could be wrong) that if Earth was a flat disc and you are located away from the center, then an object falling from a high altitude, straight over your head, would not fall perpendicularly to the surface of the…"
8 hours ago
Jim Maloy replied to Vincent Granville's discussion Help needed to prove that Earth is not flat
"The shapes of the object & the Earth can have an effect on the trajectory of the fall, because of the difference between center of mass & center of gravity."
11 hours ago
Prasanth liked Vincent Granville's blog post Book: Data Science for the Layman: No Math Added
16 hours ago
John L. Ries replied to Vincent Granville's discussion Help needed to prove that Earth is not flat
"Getting back to the original topic, I'm quite certain that flat earthers unanimously reject Einstein's relativity theories out of hand.  After all, the strongest evidence that the earth is flat is that objects fall to the ground."
18 hours ago
Prasanth liked Vincent Granville's blog post 30 Free Courses: Neural Networks, Machine Learning, Algorithms, AI
19 hours ago
Mab Alam replied to Vincent Granville's discussion Help needed to prove that Earth is not flat
"I thought that whether an object will fall on another depends on how much space (aka space-time) is warped around it. In theory should the shape matter, or just the mass? Found some interesting images in Google by searching "space time…"
22 hours ago
Tim Matteson liked Vincent Granville's discussion Help needed to prove that Earth is not flat
yesterday
Lava Kafle liked Vincent Granville's blog post Elements of Modern Data Science, AI, Big Data and ML
yesterday
tarek Jan liked Vincent Granville's blog post Comprehensive Repository of Data Science and ML Resources
yesterday
Prasanth liked Vincent Granville's blog post What is Regression Analysis?
yesterday
Vincent Granville posted a blog post

How Data Scientists Spend their Time - Nice Cartoon

Data scientists spend 80% of their time preparing and cleaning their data. They spend the other 20% of their time complaining about preparing and cleaning their data.This was posted by Kirk Borne on his Twitter account. Not sure who created the cartoon. Do we all spend 80% on our time on something, and the remaining 20% on something else? In my case, I spend 20% of my time writing articles (usually research articles that the layman can understand, and sometimes articles like this one.) The…See More
yesterday
Karthik Sirasanagandla liked Vincent Granville's blog post My Data Science Book - Table of Contents
Sunday
Ionut Motoc liked Vincent Granville's blog post What is Regression Analysis?
Sunday
Mohamed Mokhtar liked Vincent Granville's blog post Interesting Data Science Application: Steganography
Sunday
Mohamed Mokhtar liked Vincent Granville's discussion Defeating Email Monitoring Algorithms
Sunday

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 

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Vincent Granville's Blog

How Data Scientists Spend their Time - Nice Cartoon

Posted on April 22, 2018 at 4:00pm 0 Comments

Data scientists spend 80% of their time preparing and cleaning their data. They spend the other 20% of their time complaining about preparing and cleaning their data.

This was posted by Kirk Borne on his Twitter account. Not sure who created the cartoon. Do we all spend 80% on our time on something, and the remaining 20% on something else? In my case, I spend 20% of my time writing articles (usually research articles that the layman can understand, and sometimes articles like…

Continue

Two Questions to Ask to a PhD Candidate for a Leadership Role

Posted on April 21, 2018 at 3:30pm 0 Comments

These are not business questions, but soft questions that should make any PhD candidate relaxed, even intrigued, and open to talk freely. There is no wrong answer, these are open questions, but some answers could hint that the candidate is still in his/her PhD bubble, feeling superior, not flexible, and unable to see the big picture behind the apparently innocent question. These questions were asked discretely, none of the responders knew about my PhD mathematical background. …

Continue

Weekly Digest, April 23

Posted on April 21, 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
  • SQL + Notebooks + Charts. All in one platform. …
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Four Great Pictures Illustrating Machine Learning Concepts

Posted on April 20, 2018 at 1:00pm 0 Comments

Four pictures were posted recently on Data Science Central, and have immediately become popular. They are designed as one-page tutorials on some specific (basic or advanced) topics. Click on the links below to find those related to the subjects that you are interested in. 

Four Great Pictures Illustrating Machine Learning Concepts

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