Finding Ghosts in Your Data

This page serves as a compendium for all blog posts dedicated to the book Finding Ghosts in Your Data: Anomaly Detection Techniques with Examples in Python (Apress, forthcoming).

Image Contrast and Color in Print

In the process of writing chapter 2 of Finding Ghosts in Your Data, I used quite a few images to tell a story. I’ve used many of these images in other contexts, but ended up needing to make changes to increase contrast and deal with the lack of color. Forthwith are two examples. Example 1: […]

Interesting Resources for Chapter 1

For each chapter in Finding Ghosts in Your Data, I’ll include a few resources that I found interesting. This isn’t a bibliography, strictly speaking, as I might not use all of these in the course of writing, but they were at least worth noting. Books Anomaly Detection Principles and Algorithms by Mehrotra, et al. I’ll […]

Outliers, Anomalies, and Noise

This is part of the series Finding Ghosts in Your Data. For the inaugural post in this series, I want to spend a few moments on terminology. What’s the difference between an “outlier” and an “anomaly”? The interesting thing is that there’s no clear delineation in the literature. As a quick example, Mehrotra, et al, […]