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Vincent Granville's Discussions
Generalized Coefficient of Correlation for Non-Linear Relationships
Started this discussion. Last reply by Timothy Gardner Feb 17, 2018. 2 Replies 2 Likes
Hiking Challenge
Started this discussion. Last reply by James Hillstrand Feb 27, 2017. 5 Replies 0 Likes
Vincent Granville's Page
Latest Activity
Vincent Granville posted a blog postUnderstanding the foundations of Deep Learning through Linear Regression
Vincent Granville posted a blog post5 Predictions about Data Science, Machine Learning, and AI for 2019
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
Great Sunday Reading
Posted on January 20, 2019 at 12:15pm 0 Comments 0 Likes
Understanding the foundations of Deep Learning through Linear Regression
Posted on January 16, 2019 at 9:48am 0 Comments 0 Likes
This article was written by Ajit Joakar.
In this longish post, I have tried to explain Deep Learning starting from familiar ideas like machine learning. This approach forms a part of my forthcoming book. I have used this approach in my teaching. It is based on ‘learning by exception,' i.e. understanding one concept and it’s limitations and then understanding how the subsequent concept…
Continue 5 Predictions about Data Science, Machine Learning, and AI for 2019
Posted on December 20, 2018 at 6:30pm 0 Comments 0 Likes
Summary: Here are our 5 predictions for data science, machine learning, and AI for 2019. We also take a look back at last year’s predictions to see how we did.
It’s that time of year again when we do a look back in order to offer a look forward. What trends will speed up, what things will actually happen,…
New Books in AI, Machine Learning, and Data Science
Posted on December 1, 2018 at 6:26pm 0 Comments 1 Like
We are in the process of writing and adding new material (compact eBooks) exclusively available to our members, and written in simple English, by world leading experts in AI, data science, and machine learning. In the upcoming months, the following will be added:
- The Machine Learning Coding Book
- Off-the-beaten-path Statistics and Machine Learning Techniques
- Encyclopedia of Statistical Science
- Original Math, Stat and Probability Problems - with…
Things that Aren’t Working in Deep Learning
Posted on November 21, 2018 at 10:00am 0 Comments 0 Likes
Summary: This may be the golden age of deep learning but a lot can be learned by looking at where deep neural nets aren’t working yet. This can be a guide to calming the hype. It can also be a roadmap to future opportunities once these barriers are behind us. The full article is accessible here, below is a…
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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
scaling up for high dimensional data& high speed data streams..
Thanks for the invite!
Thanks for the invite!
vincent,
thanks for adding me. can i ask you why you choose to add people like me? didn't see it coming?
regards,
shane
Vincent
Thanks a ton for the friendship, it matters a lot, so happy to accept your hand of friendship
Cheers & Regards
Madhusudan
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
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
Thanks Vincent! I am honored to be your friend.
Cheers,
Vickie
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