The majority of industry and academic numeric predictive projects deal with deterministic or point forecasts of expected values of a random variable given some conditiona...
Fish schools, bird flocks, and bee swarms. These combinations of real-time biological systems can blend knowledge, exploration, and exploitation to unify intelligence and...
In my first article on this topic (see here) I introduced some of the complex stochastic processes used by Wall Street data scientists, using a simple approach that can ...
In my first article on this topic (see here) I introduced some of the complex stochastic processes used by Wall Street data scientists, using a simple approach that can b...
1 Introduction Credit risk or credit default indicates the probability of non-repayment of bank financial services that have been given to the customers. Credit risk has ...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, ...
Data classification is the central data-mining technique used for sorting data, understanding of data and for performing outcome predictions. In this small blog we will u...
If you’ve been studying artificial intelligence and its growth, you’ll know that the industry is well past its nascent stage now. There is significant maturity in its...
Having my newsfeed cluttered with articles about Google creating an AI that beats hospitals by predicting death with 95% accuracy (or some other erroneous claim), I dug u...
Recently (6/8/2018), I saw a post about a new R package “naniar”, which according to the package documentation, “provides data structures and functions ...