While this looks like a basic problem, it is actually somewhat more complicated than expected. One might think of generating uniform deviates for the longitude, as well as uniform deviates for the…Continue
People complain that governments or hackers are reading our messages for nefarious purposes. Of course this "reading" is done automatically, in large volume, by machines and NLP (natural language…Continue
Many unscrupulous bloggers re-post copyrighted material on their blogs, without permission. The problem is compounded by the fact that Google can give credit to the illegal version, and erroneously…Continue
This is our new challenge of the week. Previous challenges…Continue
Well rounded, visionary data scientist 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.
A while back, I was reading an article posted on Facebook, about Clovis people found alive and well living in Florida, with a picture featuring tribesmen (see below.) The quality of the picture was poor, and the URL was very suspicious: baynews9.com.ddwg.clonezone.link, as to make it appear that it was from Baynews9.com. It turned out that the picture (and thus the whole story) was fake: these people are real…Continue
Here are a few challenges for the mathematically inclined - most data scientists are. This is just fun problems if you have some time to kill. The first problem is about seasons in binary star planetary systems: it has implications on whether such planets are inhabitable. It is also related to time series with double periodicity. The next problems are related to infinite products, with an emphasis on building a prime-generating or at least prime-detection function. Large prime numbers are…Continue