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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

Continue

 

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

Anthony Fiedler liked Vincent Granville's blog post New Coursera Series: Machine Learning for Everyone
yesterday
Mugi Astuti liked Vincent Granville's blog post New Books and Resources for DSC Members
Monday
Vincent Granville's blog post was featured

Weekly Digest, September 21

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.  AnnouncementHow to Automate your…See More
Monday
Vincent Granville commented on Vincent Granville's blog post Difference Between Correlation and Regression in Statistics
"Thank you Omer, I fixed the mistake."
Friday
Omer Sayli commented on Vincent Granville's blog post Difference Between Correlation and Regression in Statistics
"Hi, In the first paragraph, there is  a mistake.  In regression analysis, the dependent variable is denoted "Y" and the independent variables are denoted by "X".  But it is stated…"
Friday
Vincent Granville posted blog posts
Thursday
Olivier Nayraguet commented on Vincent Granville's blog post New Books and Resources for DSC Members
"I wish I could try your restaurant as well. But I live on the East Coast. Transitioning to ML, AI, and DS. Your site is full of the best resources."
Thursday
Olalekan Ayinde liked Vincent Granville's blog post New Books and Resources for DSC Members
Thursday
Michael Fernandez replied to Vincent Granville's discussion Top 10 Machine Learning Algorithms
"Here's another very interesting writeup from Towardsdatascience.com. Posting its gist here -  1. Linear Regression: Linear regression is a supervised learning algorithm and tries to model the relationship between…"
Sep 14
Vincent Granville posted a blog post

K-Nearest Neighbors (KNN): Solving Classification Problems

Originally posted by Michael Grogan. In this tutorial, we are going to use the K-Nearest Neighbors (KNN) algorithm to solve a classification problem. Firstly, what exactly do we mean by classification?Classification across a variable means that results are categorised into a particular group. e.g. classifying a fruit as either an apple or an orange.The KNN algorithm is one the most basic, yet most commonly used algorithms for solving classification problems. KNN works by seeking to minimize the…See More
Sep 13
Vincent Granville's blog post was featured

Weekly Digest, September 14

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.  Announcements30-Day Trial: Pentaho…See More
Sep 13
Carla Sofia Rocha da Silva commented on Vincent Granville's blog post Weekly Digest, September 7
"Vincent ...picture of the week..the best really"
Sep 10
Vincent Granville posted a blog post
Sep 10
Vincent Granville's blog post was featured

Weekly Digest, September 7

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 Technical Contributions …See More
Sep 6
Vincent Granville posted a blog post

Thursday News, September 3

Here is our selection of featured articles and technical resources posted since Monday:Technical ResourcesModel Fitting Tests You've Probably Never Heard OfWhich ML / deep learning algorithm to use by problem type…See More
Sep 3
Vincent Granville's blog post was featured

Weekly Digest, August 31

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 Technical Contributions …See More
Aug 30

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, September 21

Posted on September 20, 2020 at 3:30pm 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.  

Announcement…

Continue

New Coursera Series: Machine Learning for Everyone

Posted on September 17, 2020 at 8:31am 0 Comments

After three courses, you will be able to:

  • Lead ML: Manage or participate in the end-to-end implementation of machine learning
  • Apply ML: Identify the opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and much more
  • Greenlight ML: Forecast the effectiveness of and scope the requirements for a…
Continue

Thursday News, September 17

Posted on September 17, 2020 at 8:30am 0 Comments

This is our list of featured articles and resources posted since Monday:

Announcement

Resources

Continue

K-Nearest Neighbors (KNN): Solving Classification Problems

Posted on September 13, 2020 at 2:00pm 0 Comments

Originally posted by Michael Grogan. 

In this tutorial, we are going to use the K-Nearest Neighbors (KNN) algorithm to solve a classification problem. Firstly, what exactly do we mean by classification?

Classification across a variable means that results are categorised into a particular group. e.g. classifying a fruit as either an apple or an orange.

The KNN algorithm is one the most basic, yet most commonly used…

Continue
 
 
 

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