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Vincent Granville Male Issaquah, WA United States: Like

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Blog Posts (752)
Discussions (2905)

Vincent Granville's Discussions

Outliers in Logistic Regression

Started Apr 4 0 Replies 0 Likes

Powerful, Hybrid Machine Learning Algorithm with Excel Implementation

Started Jun 12, 2018 0 Replies 0 Likes

Question about Some Statistical Distributions (Updated)

Started Feb 12, 2018 0 Replies 0 Likes

Generalized Coefficient of Correlation for Non-Linear Relationships

Started this discussion. Last reply by Timothy Gardner Feb 17, 2018. 2 Replies 2 Likes

Two Great Courses on Deep Learning and AI

Started Aug 10, 2017 0 Replies 0 Likes

Hiking Challenge

Started this discussion. Last reply by James Hillstrand Feb 27, 2017. 5 Replies 0 Likes

Challenge: Representation of Numbers as Infinite Products

Started Jan 4, 2017 0 Replies 0 Likes

Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics

Started Jan 3, 2017 0 Replies 0 Likes

Your Guide to Master Hypothesis Testing in Statistics

Started Jan 2, 2017 0 Replies 0 Likes

R moves up to 5th place in IEEE language rankings

Started Jan 2, 2017 0 Replies 0 Likes

Great Saturday Reading - Best of the Week

Started Dec 17, 2016 0 Replies 0 Likes

Deep Learning in Python: Getting Started

Started Dec 10, 2016 0 Replies 0 Likes

Great Weekend Reading

Started Nov 12, 2016 0 Replies 0 Likes

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Vincent Granville posted a blog post

10 Visualizations Every Data Scientist Should Know

This article is by Jorge Castañón, Ph.D., Senior Data Scientist at the IBM Machine Learning Hub.Data visualization plays two key roles:1. Communicating results clearly to a general audience.2. Organizing a view of data that suggests a new hypothesis or a next step in a project.It’s no surprise that most people prefer visuals to large tables of numbers. That’s why clearly labeled plots with meaningful interpretation always make it to the front of academic papers.…See More

Tuesday

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Vincent Granville posted a blog post

More Weird Statistical Distributions

Some original and very interesting material is presented here, with possible applications in Fintech. No need for a PhD in math to understand this article: I tried to make the presentation as simple as possible, focusing on high-level results rather than technicalities. Yet, professional statisticians and mathematicians, even academic researchers, will find some deep and fascinating results worth further exploring.…See More

Oct 26

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Vincent Granville posted a blog post

Complete Hands-Off Automated Machine Learning

By Bill Vorhies. Summary: Here’ a proposal for real ‘zero touch’, ‘set-em-and-forget-em’ machine learning from the researchers at Amazon. If you have an environment as fast changing as e-retail and a huge number of models matching buyers and products you could achieve real cost savings and revenue increases by making the refresh cycle faster and more accurate with automation. This capability likely will be coming soon to your favorite AML platform.…See More

Oct 22

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Vincent Granville's blog post was featured

40+ Modern Tutorials Covering All Aspects of Machine Learning

This list of lists contains books, notebooks, presentations, cheat sheets, and tutorials covering all aspects of data science, machine learning, deep learning, statistics, math, and more, with most documents featuring Python or R code and numerous illustrations or case studies. All this material is available for free, and consists of content mostly created in 2019 and 2018, by various top experts in their respective fields. A few of these documents are available on LinkedIn: see last section on…See More

Oct 13

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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) 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 (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. 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.

My Website or LinkedIn Profile (URL):: http://www.linkedin.com/in/vincentg

Field of Expertise:: Data Mining, Marketing Databases, Web Analytics, Statistical Consulting, Other

Years of Experience in Analytical Role:: 15+

Professional Status:: C-Level

Interests:: Networking, New Venture, Other

What is your Favorite Data Mining or Analytical Website?: http://www.analyticbridge.com

What Other Analytical Website do you Recommend?: http://www.datasciencecentral.com

Your Company:: Data Shaping Solutions

Industry:: Internet

How did you find out about AnalyticBridge?: Founder

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Vincent Granville's Blog

10 Visualizations Every Data Scientist Should Know

Posted on November 12, 2019 at 10:00am 0 Comments 0 Likes

This article is by Jorge Castañón, Ph.D., Senior Data Scientist at the IBM Machine Learning Hub.

Data visualization plays two key roles:

1. Communicating results clearly to a general audience.

2. …

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More Weird Statistical Distributions

Posted on October 26, 2019 at 6:00pm 0 Comments 0 Likes

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Complete Hands-Off Automated Machine Learning

Posted on October 22, 2019 at 2:30pm 0 Comments 0 Likes

By Bill Vorhies.

Summary: Here’ a proposal for real ‘zero touch’, ‘set-em-and-forget-em’ machine learning from the researchers at Amazon. If you have an environment as fast changing as e-retail and a huge number of models matching buyers and products you could achieve real cost savings and revenue increases by making the refresh cycle faster and more accurate with automation. This capability likely will be coming soon to your favorite AML…

Continue

40+ Modern Tutorials Covering All Aspects of Machine Learning

Posted on October 13, 2019 at 11:00am 0 Comments 0 Likes

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Surprising Uses of Synthetic Random Data Sets

Posted on October 2, 2019 at 5:00pm 0 Comments 0 Likes

I have used synthetic data sets many times for simulation purposes, most recently in my articles Six degrees of Separations between any two Datasets and How to Lie with p-values. Many…

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Comment Wall (79 comments)

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At 6:48pm on December 13, 2018, Victor Zurkowski said…: Dear Vincent,

I want to let you know that appreciate your posts. Your excursions in data science, number theory, probabilities, experimental mathematics, etc. are thoughtful, provocative, on occasions infuriating opinionated, and never dull. I also admire how prolific you are.

Here's to many more blog entries,

Victor

At 1:15am on June 24, 2013, Hina Ranglani said…: sir,looking for a answer how
scaling up for high dimensional data& high speed data streams..

At 4:07am on April 12, 2013, Nene Lawani said…: Thanks Vincent! Sorry I missed this earlier...

At 4:06pm on March 10, 2013, Serge Kozlov said…: Thanks for the invite!

At 10:52am on March 10, 2013, Robert Downing said…: Thanks for the invite!

At 3:41am on March 9, 2013, Shane Campbell said…: vincent,

thanks for adding me. can i ask you why you choose to add people like me? didn't see it coming?

regards,

shane

At 6:37am on February 21, 2013, hunter.robertallan said…: Thanks also for the invite. I do have a question about data mining methods and tools. I have a specific situation in mind at work, and would like some professional feedback. Anyone willing to lend an ear and opinion..? thanks...rob

At 4:01am on February 17, 2013, Rishi Jain said…: Hey Vincent,

Sometime back I saw internship material on your site. I am working in the Analytics Industry and looking for improving my technical skills. Please let me know in case you guys are offering any internships which I can pursue along with my job.

Regards,

Rishi

At 3:04pm on December 19, 2012, Vickie Comrie said…: Thanks Vincent! I am honored to be your friend.

Cheers,

Vickie

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