# Monthly Archives: September 2017

## Naive Bayes explained naively

To me, reading about the concept of naive Bayes is like following a very logical train of thought. Without really knowing (or caring) whether this is an accurate description, I call something like this a logic chain… and it goes … Continue reading

## Create an automated ML model evaluation report with scikit-learn, matplotlib and python-docx

As my knowledge on the subject of machine learning grows, I ended up writing code for several different models several times over. In order to better evaluate which model performs better, I wanted an automated ML model evaluation report that … Continue reading

## Kaggle Learnings – Exploratory Data Analysis & Data Cleaning

I am a strong believer in worked examples and case studies. Theory is all nice and well, but without applying it in a real use-case, it can be quite a pointless exercise. Today on Kaggle, I came across a worked … Continue reading

## Linear Regression in a Nutshell

Explaining linear regression using the ordinary least squares method appears to be a bit of a rite of passage in data science judging by the amount of entries one can find on the web. True enough, it has the same … Continue reading