There is a set of techniques covering all aspects of machine learning (the statistical engine behind data science) that does not use any mathematics or statistical theory...
Neural networks are considered complicated and they are always explained using neurons and a brain function. But we do not need to learn how to brain works to understand ...
This article comes from Toodarkpark. Below is an extract, covering a few of the programming languages listed in the original article. The proliferation of modern programm...
A Practical Implementation Guide to Predictive Data Analytics Using Python Covers basic to advanced topics in an easy step-oriented manner Concise on theory, strong focus...
“We want to predict -X-.” Fill in any desirable topic on the location of the X and you have the formulation of a use-case in the way many companies today think about ...
In the first post in this series on Artificial Intelligence: Monster or Mentor? we saw that there are several key ways in which AI advances can improve human productivity...
Businesses across the globe are facing the brunt, one of huge data influx and second of increasing data complexity and of course the market volatility. To address these c...
Introduction Much of the recent AI revolution has been focused on automation through big data and/or sensors and feedback into neural networks. The resulting applications...
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...
One of the best ways to learn about any topic is start with very fundamental questions like What, Why etc? Good old Socratic method. In this series of articles on data mi...