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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 Emanuel Woiski Dec 30, 2017. 6 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, 2017. 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, 2017. 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, 2017 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

David Quesada liked Vincent Granville's blog post Learn Python in 3 days : Step by Step Guide
12 hours ago
Frederick T Williams liked Vincent Granville's blog post The Fundamentals of Data Science
23 hours ago
Lior Shamir liked Vincent Granville's blog post How and Why: Decorrelate Time Series
yesterday
Vincent Granville's blog post was featured

Weekly Digest, January 22

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 ContributionsWhat Happens when our Computers get Smarter than we are? …See More
Saturday
Vincent Granville posted a blog post

Weekly Digest, January 22

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 ContributionsWhat Happens when our Computers get Smarter than we are? …See More
Saturday
ANISH XAVIER liked Vincent Granville's blog post Number Theory: Nice Generalization of the Waring Conjecture
Saturday
Prabhakaran Sampath liked Vincent Granville's blog post Creating Your First Machine Learning Classifier with Sklearn
Saturday
Veena Ghorakavi commented on Vincent Granville's blog post DSC Competition for Data Science and Quant Pros - $2,000 Award
"Is there a chance for a similar competition to happen in 2018?"
Saturday
Veena Ghorakavi liked Vincent Granville's blog post DSC Competition for Data Science and Quant Pros - $2,000 Award
Saturday
Brandon M Stephan liked Vincent Granville's group Data Science Certification
Friday
Vincent Granville posted a blog post
Thursday
RAGHAVENDRACHARI liked Vincent Granville's blog post Selected Recent Articles from Top DSC Contributors - Part 3
Thursday
Kaushal Bhatt and Vincent Granville are now friends
Thursday
Frederick T Williams liked Vincent Granville's blog post A Simple Introduction to Complex Stochastic Processes
Wednesday
paul c liked Vincent Granville's blog post 140 Machine Learning Formulas
Wednesday
Duane Baker liked Vincent Granville's blog post Creating Your First Machine Learning Classifier with Sklearn
Wednesday

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, January 22

Posted on January 20, 2018 at 1:00pm 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

Thursday News: AI, IoT, Machine Learning, BI, Conferences, Python

Posted on January 18, 2018 at 9:30am 0 Comments

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

Resources::

Continue

10 Great Articles about Stochastic Processes and Related Topics

Posted on January 16, 2018 at 7:00pm 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,…

Continue

Creating Your First Machine Learning Classifier with Sklearn

Posted on January 16, 2018 at 9:30am 0 Comments

This article was written by Kasper Fredenslund.

At the end of the post you will know how to:

  • Import and transform data from a .csv file to use with sklearn
  • Inspect the dataset and select relevant features
  • Train different classifiers on the data using sklearn
  • Analyse the results with the intention of improving your model

Importing data

Once…

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