This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, c...
Contributed by Yannick Kimmel. He is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between April 11th to ...
Actually, this is about two R versions (standard and improved), a Python version, and a Perl version of a new machine learning technique recently published here. We aske...
When dealing with time series, the first step consists in isolating trends and periodicites. Once this is done, we are left with a normalized time series, and studying th...
More and more people are talking about the new economy, and in particular, the role played by robots. As jobs are being eliminated and replaced by robots, governments are...
Summary: Looking beyond today’s commercial applications of AI, where and how far will we progress toward an Artificial Intelligence with truly human-like reasoning an...
Actually, this is about two R versions (standard and improved), a Python version, and a Perl version of a new machine learning technique recently published here. We asked...
Recently we read a lot about fake news, alternate facts and journalism lies. Companies like Facebook develop data science algorithms to detect these postings, based amon...
Guest blog post by Wale Akinfaderin, PhD Candidate in Physics. In the last few months, I have had several people contact me about their enthusiasm for venturing into t...
Summary: In our recent article on “5 Types of Recommenders” we failed to mention Indicator-Based Recommenders. These have some unique features and ease of impleme...