Data scientists spend 80% of their time on data cleaning and exploratory analysis. What if you could automate most of this? What if data scientists… Read More »How to Automate Data Cleaning, in a Nutshell
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).
In the first part here, I discussed missing, outdated and unobserved data, data that is costly to produce, as well as dirty, unbalanced and unstructured… Read More »15 Data Issues and How to Fix Them – Second Part
This article is intended to users relying on machine learning solutions offered by third party vendors. It applies to platforms, dashboards, traditional software, or even external pieces of code that are too time consuming to modify. One of the goals is to turn such systems into explainable AI.
Say you need to implement some machine learning system. Should you purchase a product, re-use open-source code, or develop your own algorithms? The decision does… Read More »Reinventing or Reusing? Home-made vs Third-party Solutions
After 25 Years of Coding in C And Perl. As an independent author/researcher, there is of course nothing in my “job description” that says I… Read More »Lessons Learned from Writing My First Python Script