Summary: What are the earliest seeds of artificial intelligence? To whom do we owe thanks for starting us down this path? Many modern researchers to be sure, but th...
There’s no better source for tricks of the analytics trade than Dr. John Elder, the established industry leader renowned as an acclaimed training workshop instructo...
This article was written by Natasha Latysheva. Here we publish a short version, with references to full source code in the original article. Our internal data scienti...
Summary: Can AI take its victory lap in 2016? A lot depends on what you call AI and whether the consumer can perceive it. Image source: skymind.io If 2016 is to be ...
Summary: Picking an analytic platform when first starting out in data science almost always means working with what we’re most comfortable. But as organizations grow ...
Summary: Want to win a Kaggle competition or at least get a respectable place on the leaderboard? These days it’s all about ensembles and for a lot of practitioners t...
As a data scientist, your job doesn’t always make sense to others. Ever tried explaining what you do to your parents? They may nod their heads, but their eyes scream co...
Guest blog post by Vincent Granville AI was very popular 30 years ago, then disappeared, and is now making a big come back because of new robotic technolo...
As part of Data Science tutorial Series in my previous post I posted on basic data types in R. I have kept the tutorial very simple so that beginners of R programming ...
Summary: Proof of Concept projects are a popular place to start but they may be the wrong solution. To ensure success focus on Proof of Value and alignment with the c...