Cosine similarity measures the similarity between two non-zero vectors by calculating the cosine of the angle between them. Here's the basics behind cosine similarity and how it is used across different areas of machine learning.
Benford’s Law states that digits with smaller values are more likely to be the lead digit in a data set than digits with larger values. Here’s when to use the law, when not to use it and why it matters.
Statistical analysis is the process of collecting and analyzing data using statistical methods to uncover trends, develop meaningful data insights and tell quantitative stories.
Data integrity means data is collected in a compliant manner, accurate, complete and consistent throughout its lifecycle. Here’s why it’s important and the main types of data integrity to know.
Regression to the mean is a statistical phenomenon where rare or extreme events are likely to be followed by more typical ones. Over time, outcomes regress to the average or mean.
Graph theory is the study of graph data structures, which model object relationships using vertices connected by edges. It is a helpful tool to quantify and simplify complex systems.
Dynamic time warping (DTW) is a technique used to compare two temporal sequences that don’t perfectly sync. Here’s how it works, how to implement it and its key benefits.
A neural network is a series of algorithms that identifies patterns and relationships in data, similar to the way the brain operates. Here's how they work.
