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

Question: High Precision Computing in Python or R

Started this discussion. Last reply by Matthew Boerner on Wednesday. 4 Replies

I am trying to make some simulations of chaotic systems, for instance X(k) = 4 X(k) (1 - X(k-1)) but I noticed that for all these systems, the loss of precision propagates exponentially, to the point…Continue

Machine Learning Algorithm to Trade Bitcoin

Started this discussion. Last reply by Vincent Granville Nov 11. 4 Replies

I am wondering if you can trade Bitcoin on a trading platform like Coinbase.com or Avatrade, using your own…Continue

40-year old trick to clean data efficiently, and perform fuzzy matching

Started this discussion. Last reply by Erick Costa Damasceno Oct 10. 4 Replies

While much of data cleaning is performed before loading data in a database (especially for one-time, ad hoc analyses), there is a way to do it, continuously (like once a week or once a day), once the…Continue

Our Solar System Does Not Have a Center

Started Jun 12 0 Replies

Just for the curious. This is not a data science problem.I was reading an article in National Geographic, entitled…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

Vincent Granville posted a blog post

Weekly Digest, November 20

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.Featured Resources and Technical Contributions…See More
8 hours ago
Prasanth liked Vincent Granville's discussion 40-year old trick to clean data efficiently, and perform fuzzy matching
22 hours ago
Vinod Sharma liked Vincent Granville's discussion Top 10 Machine Learning Algorithms
yesterday
Paulo César liked Vincent Granville's blog post Python, Machine Learning, and Language Wars. A Highly Subjective Point of View
yesterday
Prasanth liked Vincent Granville's blog post Learning R in Seven Simple Steps
yesterday
Roman Radchenko commented on Vincent Granville's blog post Free Deep Learning Book (MIT Press)
"Thanks a lot. Book (Russian translation). Book"
yesterday
Robert Lucente replied to Vincent Granville's discussion Coverage problem for cell phone towers
"I am interested in the relation to the 4 color problem. When you get a chance, please elaborate."
yesterday
Vincent Granville's blog post was featured

Programming Languages for Data Science and ML - With Source Code Illustrations

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, AI and many more.…See More
Thursday
Vincent Granville posted blog posts
Thursday
Jean-Charles Forszpaniak commented on Vincent Granville's blog post Free Book: SQL Essentials
"The title appears in the section "books", but it's $8, and availble on Amazon (not free as stated)."
Thursday
Eltahir Ibrahim Elnour Salim liked Vincent Granville's blog post Black-box Confidence Intervals: Excel and Perl Implementation
Wednesday
Matthew Boerner commented on Vincent Granville's blog post Fascinating Chaotic Sequences with Cool Applications
"I posted a Java version of the algorithm at https://www.datasciencecentral.com/forum/topics/question-how-precision-computing-in-python using the same seed.  Sequence diverges from the correct value at iteration #30 using my Java…"
Wednesday
Matthew Boerner replied to Vincent Granville's discussion Question: High Precision Computing in Python or R
"Here's a Java version.  You should find your own implementation of bigSqrt.  This Java version diverges from the correct answer at iteration #30.  I was hoping it would be better.  Unfortunately Java does not have a built-in…"
Wednesday
Rick Liao liked Vincent Granville's discussion Question: High Precision Computing in Python or R
Wednesday
Duane Baker liked Vincent Granville's blog post Data Driven Leader by Jenny Dearborn, CLO and SVP at SAP
Wednesday
Tim Matteson liked Vincent Granville's discussion Question: High Precision Computing in Python or R
Tuesday

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 

Vincent Granville's Videos

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Vincent Granville's Blog

Weekly Digest, November 20

Posted on November 18, 2017 at 7:30am 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.

Featured Resources and Technical Contributions…

Continue

Programming Languages for Data Science and ML - With Source Code Illustrations

Posted on November 16, 2017 at 2:36pm 0 Comments

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, AI and…

Continue

Data Driven Leader by Jenny Dearborn, CLO and SVP at SAP

Posted on November 14, 2017 at 9:41am 0 Comments

Jenny Dearborn is the Chief Learning Officer and Senior Vice President at SAP. As global Chief Learning Officer for the 67,000 employees at SAP, Jenny leads an internationally-acclaimed and award-winning team recognized as the #1 performing corporate learning department in the world by eLearning Magazine.

Jenny is a recognized thought leader in human capital management and general business, and is a regular contributor to Forbes, Wall Street Journal, The…

Continue
 
 
 

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