R is a powerful language. From its ability to create complex statistical models with a few lines of code to its robust graphical capabilities and stunning data visualizations - R is a very handy…Continue
Here is our list, in random order. Click on any link to discover recent articles on these topics: we add new content each week.…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.
Here is our updated list of top Data Science Central (DSC) resources, including reference articles and tutorials, top categories, tools and techniques, as well as several useful links (jobs, events, training, webinars, books and so on) and information about our popular newsletter. You will also find information about blogging with us, or where to find us on Facebook, LinkedIn or Twitter.
This reference is a part of a new series of DSC articles, offering selected tutorials, references/resources, and interesting articles on subjects such as deep learning, machine learning, data science, deep data science, artificial intelligence, Internet of Things, algorithms, and related topics. It is designed for the busy reader who does not have a lot of time digging into long lists of advanced publications.…Continue
Many people new to data science might believe that this field is just about R, Python, Hadoop, SQL, and traditional machine learning techniques or statistical modeling. Below you will find fundamental articles that show how modern, broad and deep the field is. Some data scientists are actually doing none of the above. In my case, I don't even code, but instead, I make various applications talk to each other, in a machine-to-machine communication framework. It is true though that most data…Continue