Author and Publisher at MLtechniques.com. Machine learning scientist, mathematician, book author (Wiley), patent owner, former post-doc at Cambridge University, former VC-funded executive, with 20+ years of corporate experience including CNET, NBC, Visa, Wells Fargo, Microsoft, eBay. Vincent also founded and co-founded a few start-ups, including one with a successful exit (Data Science Central acquired by Tech Target).
This question was recently posted on Quora: What is a full stack data scientist? Below is my answer. Most answers focus on the technical skills… Read More »Full Stack Data Scientist: The Elusive Unicorn and Data Hacker
Guest blog post by Zied HY. Zied is Senior Data Scientist at Capgemini Consulting. He is specialized in building predictive models utilizing both traditional statistical methods (Generalized Linear… Read More »Sequence Modeling with Neural Networks – Part I
Updated on Dec 12, 2018. An error was fixed when g(x) is not equal to x, and a new section “Generalization” was added. A link… Read More »Some Irresistible Integrals, Computed Using Statistical Concepts
The impact of a change of scale, for instance using years instead of days as the unit of measurement for one variable in a clustering… Read More »Scale-Invariant Clustering and Regression
The impact of a change of scale, for instance using years instead of days as the unit of measurement for one variable in a clustering… Read More »Scale-Invariant Clustering and Regression
In this article, we show that the issue with polynomial regression is not over-fitting, but numerical precision. Even if done right, numerical precision still remains… Read More »Deep Dive into Polynomial Regression and Overfitting
In this article, we show that the issue with polynomial regression is not over-fitting, but numerical precision. Even if done right, numerical precision still remains… Read More »Deep Dive into Polynomial Regression and Overfitting
In Part 1 of this article (see here) we featured the two results below, as well as a simple way to prove these formulas. Here,… Read More »Two Beautiful Mathematical Results – Part 2
Here are some recommended books for data science practitioners, covering machine learning, deep learning, business intelligence, forecasting, text analytics and much more. Book Repository for… Read More »Reading List for Data Scientists
I wrote about this long ago (see here in 2014), and so did many other practitioners. This new post shows more maturity I think, a more… Read More »Four Types of Data Scientists
