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

Data science workstation vs. cloud service provider or via on on-premises data center.

Started this discussion. Last reply by Vincent Granville Apr 13. 1 Reply

I wanted to get your thoughts on data science workstations? We’re seeing an uptick in product releases/messaging around DS workstations from several hardware vendors and I wanted to get your take on…Continue

How to deal with missing data

Started this discussion. Last reply by Prateek Baranwal Feb 6. 1 Reply

Originally posted by Vincent Ajayi. The most common challenge faced by data scientists (DS) and…Continue

Simulating Distributions with One-Line Formulas, even in Excel

Started this discussion. Last reply by Dennis Sweitzer Feb 7. 6 Replies

If you don't like using black-box R functions, or you don't have access to these functions, here are simple options to simulate deviates from various distributions. They can even be implemented in…Continue

Moments of Order Statistics

Started this discussion. Last reply by Prateek Baranwal Feb 6. 2 Replies

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Vincent Granville's Page

Profile Information

Company:
Data Science Central, AnalyticBridge
Job Title:
Executive Data Scientist, Co-Founder
Seniority:
C-Level
Industry:
Internet
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.
LinkedIn Profile:
http://www.linkedin.com/in/vincentg
Interests:
Networking, New venture, Recruiting, Other

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 liked Stephanie Glen's blog post Misleading Graphs: Avoid These Common Mistakes
yesterday
Dorothy Hewitt-Sanchez liked Vincent Granville's blog post 30 Free Courses: Neural Networks, Machine Learning, Algorithms, AI
yesterday
Vincent Granville's blog post was featured

Weekly Digest, June 1

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. To subscribe, follow this link.  AnnouncementsAmid the economic slowdown, businesses seek to reduce IT…See More
Sunday
Anthony Fiedler liked Vincent Granville's blog post New Probabilistic Approach to Factoring Big Numbers
Saturday
Rakesh Chintha liked Vincent Granville's blog post Online Encyclopedia of Statistical Science (Free)
Saturday
Rakesh Chintha liked Vincent Granville's blog post Comprehensive Repository of Data Science and ML Resources
Saturday
Charles Broming liked Vincent Granville's blog post 88 percent of all integers have a factor under 100
Thursday
Charles Broming liked Vincent Granville's blog post A Beautiful Probability Theorem
Thursday
Charles Broming liked Vincent Granville's blog post Little Proof of the Prime Number Theorem
Thursday
Charles Broming liked Vincent Granville's blog post New Probabilistic Approach to Factoring Big Numbers
Thursday
Vincent Granville posted a blog post

Thursday News, May 28

Here is our selection of featured articles and resources posted since Monday:ResourcesA Free Self-paced Learning path for ML and Deep LearningA Fundamental Theorem for Epidemiology…See More
Thursday
Lavanya B liked Vincent Granville's blog post 66 job interview questions for data scientists
Thursday
Vincent Granville's blog post was featured

New Probabilistic Approach to Factoring Big Numbers

Product of two large primes are at the core of many encryption algorithms, as factoring the product is very hard for numbers with a few hundred digits. The two prime factors are associated with the encryption keys (public and private keys). Here we describe a new approach to factoring a big number that is the product of two primes of roughly the same size. It is designed especially to handle this problem and identify flaws in encryption algorithms.  While at first glance it appears to…See More
May 27
Prasanth liked Vincent Granville's discussion Large set of Machine Learning and Related Resources
May 27
Rakesh Chintha liked Vincent Granville's blog post How to Automatically Determine the Number of Clusters in your Data - and more
May 25
Rakesh Chintha liked Vincent Granville's blog post 29 Statistical Concepts Explained in Simple English - Part 1
May 25

Comment Wall (16 comments)

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At 6:53pm on May 04, 2019, Florent Rudel Ndeffo gave Vincent Granville a gift
Gift
Thank you for the documentations. Priceless! :)
At 9:13am on December 13, 2018, victor zurkowski said…

Dear Vincent,

Do you know how long does membership approval in "Analytic Bridge" take? I want to submit an answer to the self-correcting random walk problem. The answer is long, and I left a copy of my document (not the final draft) in Github.

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/

Vincent Granville's Videos

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Vincent Granville's Blog

Weekly Digest, June 1

Posted on May 31, 2020 at 11:00am 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. To subscribe, follow this…

Continue

Thursday News, May 28

Posted on May 28, 2020 at 10:00am 0 Comments

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

Resources

Continue

New Probabilistic Approach to Factoring Big Numbers

Posted on May 27, 2020 at 8:00am 0 Comments

Product of two large primes are at the core of many encryption algorithms, as factoring the product is very hard for numbers with a few hundred digits. The two prime factors are associated with the encryption keys (public and private keys). Here we describe a new approach to factoring a big number that is the product of two primes of roughly the same size. It is designed especially to handle this problem and identify flaws in encryption algorithms.  

While at first glance it appears…

Continue

Weekly Digest, May 25

Posted on May 24, 2020 at 12:30pm 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. To subscribe, follow this link.  

Featured Resources and…

Continue
 
 
 

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