We use cluster analysis in machine learning, image analysis, data mining and pattern recognition. Here’s how it works and when you’ll find it most useful.
The Fibonacci sequence is a series of numbers in which each number equals the sum of the two that precede it. For example, 0, 1, 1, 2, 3, 5, 8, 13, 21 and so on.
Every data scientist should know how to form clusters in Python since it’s a key analytical technique in a number of industries. Here’s a guide to getting started.
Correlation occurs when two variables change at the same time, while causation is when a change in one variable causes the other to change. Here’s why you need to understand the difference.
Data divergence, meaning differences in results generated from old and new versions of data architecture, results from a number of issues in the pipeline. Fortunately, a relatively straightforward method exists for resolving the problem.
