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).
Guest blog post by Michael Li, Head of Analytics and Data Science at LinkedIn. I’m sure everyone who has been following tech industry news knows… Read More »Elements of Modern Data Science, AI, Big Data and ML
Written exclusively for Data Science Central, by Vincent Granville. These articles are intended for non-experts, written in simple English, and particularly suited for professionals managing… Read More »44 Original Data Science and Machine Learning Articles
Cambridge Analytica was caught tampering with elections by exploiting Facebook, but chances are that this is the tip of the iceberg, and that many others,… Read More »Simple Trick to Prevent Cambridge Analytica and Others to Hack into Facebook Data
The answer to this question is not black and white, and also depends on where you live, what you did during your PhD program, how… Read More »Opinion: Is a PhD helpful for a data science career?
Ajit’s research is focused on Data Science for IoT. He teaches the same at Oxford University and UPM in Madrid (@forumoxford + @citysciences). Ajit is… Read More »Ajit Jaokar Retrospective: AI, ML, IoT, Data Science Articles
What do experienced data scientists know that beginner data scientists don’t know? Here is a quick overview. Automating tasks. Writing code that writes code. Outsourcing… Read More »22 Differences Between Junior and Senior Data Scientists
This is a quote by George E Box. Share if you like it. In short, all models are approximations. All models are wrong, but some… Read More »Statisticians, like artists, have the bad habit of falling in love with their models
Summary: Automated Machine Learning has only been around for a little over two years and already there are over 20 providers in this space. However,… Read More »Next Generation Automated Machine Learning (AML)
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation,… Read More »27 Great Resources About Logistic Regression
This article is intended for practitioners who might not necessarily be statisticians or statistically-savvy. The mathematical level is kept as simple as possible, yet I… Read More »Stochastic Processes and New Tests of Randomness – Application to Cool Number Theory Problem
