XGBlog

Dealing With Missing Values, Part 3.

More Advanced Methods

Jun 7 • 

Bojan Tunguz

10

Dealing With Missing Values, Part 2.

Multivariate Imputation by Chained Equations, Indicator Variable Techniques, and Domain-Specific Rules

Jun 2 • 

Bojan Tunguz

7

May 2025

Dealing With Missing Values, Part 1.

A semi-comprehensive look at all the ways we deal with missing values in Data Science and Machine Learning

May 27 • 

Bojan Tunguz

24

March 2025

TrainXGB - Train XGBoost in Browser

The simplest way to train an XGBoost model in GUI right in your browser

Mar 6 • 

Bojan Tunguz

19

February 2025

XGBoost is All You Need - Part 7

Nontrivial use case 3: use of XGBoost for unsupervised tasks

Feb 27 • 

Bojan Tunguz

27

2

XGBoost is All You Need - Part 6

Nontrivial use case 2: use of Shapely values for feature selection and feature engineering

Feb 24 • 

Bojan Tunguz

32

2

XGBoost is All You Need - Part 5

Nontrivial use case 1: multi-GPU and multi-machine training

Feb 20 • 

Bojan Tunguz

23

1

Book Review - Effective Visualization: Exploiting Matplotlib & Pandas

Great introductory book for plotting and visualization in Python

Feb 13 • 

Bojan Tunguz

15

1

When to use which approach/technique with a given dataset

These are my rules of thumb, and caveats could fill an entire book

Feb 10 • 

Bojan Tunguz

28

2

Book Review - Machine Learning for Tabular Data

XGBoost, Deep Learning, and AI

Feb 6 • 

Bojan Tunguz

22

XGBoost is All You Need, Part 4

A Brief Intro to XGBoost

Feb 3 • 

Bojan Tunguz

32

1

January 2025

XGBoost is All You Need, Part 3 - Gradient Boosted Trees

This is the third part in the series of blog posts about XGBoost, based on my 2024 GTC presentation you can find Part 1 here, and Part 2 here.

Jan 30 • 

Bojan Tunguz

26

5