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

Correlation Coefficient in Flat Line Model

Started yesterday 0 Replies

Let say that your model is Y = a + bX, (for instance X is the time) but you know that b = 0. In short, you are trying to get the best fit for Y = a. Of course a is your average computed on your…Continue

Change of Field for Tenured University Professors

Started this discussion. Last reply by Vincent Granville on Tuesday. 2 Replies

Is it possible for a university professor to truly change fields while staying an academic in the same university? For instance from computational statistics to data science, operations research,…Continue

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

 

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

Bec liked Vincent Granville's blog post 10 types of regressions. Which one to use?
1 hour ago
Vincent Granville posted blog posts
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Prasanth liked Vincent Granville's blog post Invitation to join Data Science Central
11 hours ago
Sayantan Naha liked Vincent Granville's group Resources
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Sayantan Naha liked Vincent Granville's profile
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Sayantan Naha liked Vincent Granville's group Data Science Apprenticeship
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Sayantan Naha liked Vincent Granville's group Data Science Certification
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Oren Bochman commented on Vincent Granville's blog post Deep Learning versus Machine Learning in One Picture
"So clearly Deep learning is not machine learning Logistic regression sucks at high dimensions ML cannot deal with many local max minima. I don't think so toss the graphic in the recycle bin."
16 hours ago
Richard Cook liked Vincent Granville's blog post Comprehensive Repository of Data Science and ML Resources
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Vincent Granville's discussion was featured

Correlation Coefficient in Flat Line Model

Let say that your model is Y = a + bX, (for instance X is the time) but you know that b = 0. In short, you are trying to get the best fit for Y = a. Of course a is your average computed on your observations in that case (or better, the median if outliers are present.)But how would you measure the correlation between Y and the…See More
yesterday
Vincent Granville posted a discussion

Correlation Coefficient in Flat Line Model

Let say that your model is Y = a + bX, (for instance X is the time) but you know that b = 0. In short, you are trying to get the best fit for Y = a. Of course a is your average computed on your observations in that case (or better, the median if outliers are present.)But how would you measure the correlation between Y and the…See More
yesterday
Vincent Granville replied to AJ Goldstein's discussion What are some Data Scientist KPI's?
"Automating and outsourcing your tasks is one way to show improvement. The KPI could be time-to-delivery (for a project) or ROI if easy to measure (cost savings to your company, increased revenue thanks to your algorithm, amount of fraud eliminated,…"
yesterday
Vincent Granville replied to Nolwen Brosson's discussion Student building a career path
"PhD might not help you these days, some employers view it negatively. There are plenty of jobs in which you can leverage your business degree: BI (business intelligence, e.g. business analyst) or get hired by a consulting firm, to name a few. Other…"
yesterday
Vincent Granville replied to Stephen Pelkofer's discussion Master's Program Resume
"You might as well not use a resume, but instead have a GitHub account where you can show your portfolio (your source code and some applications.) Being active on social networks, a good LinkedIn profile, writing a few great articles (on DSC too)…"
yesterday
Vincent Granville replied to Prashanth Southekal, PhD's discussion Regression Analysis
"You could turn your categorical variables into dummy binary variables (google "dummy variable"), and then use any standard regression. This is often done in the context of logistic regression."
yesterday
Tim Matteson liked Vincent Granville's discussion Change of Field for Tenured University Professors
yesterday

Comment Wall (15 comments)

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At 3:05am on January 28, 2018, Dr S Kotrappa said…

Sir  Vincent Granville,

May I know how many till now completed DSA from DSC.

Thanking you n Regards

Dr S Kotrappa

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

Vincent Granville's Videos

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Vincent Granville's Blog

Difficult Probability Problem: Distribution of Digits in Rogue Systems

Posted on February 22, 2018 at 7:00pm 0 Comments

I recently posted a table summarizing probabilistic properties of digits in various number representation systems, see here.  The topic is already rather difficult for well-behaved systems (those listed in my table) but some systems are rogue, and do not have these nice statistical properties. Here we focus on one of these less known systems,…

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Thursday News: Correlation, Regression, R, AI, Books, Deep Learning, NLP

Posted on February 22, 2018 at 11:30am 0 Comments

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

Forum Questions and Answers

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15 Great Articles About Decision Trees

Posted on February 21, 2018 at 6:30pm 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 many more. To keep receiving these articles, …

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Selected Recent Articles from Top DSC Contributors - Part 6

Posted on February 20, 2018 at 3:30pm 0 Comments

This is a new series, featuring great content from our top contributors. Some of these articles are rather technical in nature, but many are business-oriented and written in simple English. The entire series consists of about 120 articles. We intend to publish a new set every two weeks or so. Click here to check out the…

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