Writing
Practical explanations of machine learning and data workflows, with the code, diagrams, and intermediate reasoning left in.
All articles
Feature Engineering - I
Let's dig into selecting the right features for training our models with statistics: variance-based methods, correlation-based methods, ANOVA, and the chi-square test.
Whipping Up a Neural Network from Scratch
It's a fascinating world full of algorithms, all of which have simple origins and lucid explanations. Let's see if you can get inspired enough to code your own neural networks.
Web Scraping and Preparing a Dataset
The abundance of data these days is overwhelming, and it is growing at an ever-increasing rate. How wonderful would it be if we could use a little of it for our analytics? Let's get started with some of the tools.