Heeey, welcome to Vu’s blog 👋

Hi, my name is Chan Kha Vu. I’m currently a Machine Learning engineer at Microsoft in Seattle, working on ranking models at a search engine called Bing. This blog is a place where I share my thoughts and study notes on machine learning, mathematics, and software engineering.

At the core of a Search Engine: Learning to Rank

Learning to Rank (LTR) is a core component of any recommendation system. It is the algorithm that forms the final list of items to be shown to the user. This blog post is a comprehensive introduction to the basics of LTR and Unbiased LTR. Hopefully, it will give you enough context to build your own models or to understand more recent research in the field.

Meet “Iva”, my mini Deep Learning rig

I built a cheap-ish 2x3090 RTX Deep Learning rig for my personal projects and experiments. In this post, I will share my build philosophy, inspirations, and reasoning behind my component choices.

I enabled ChatGPT to “see” images and made it play Dixit with my friends

To celebrate the week of Bing’s integration with ChatGPT, I built an AI bot based on GPT-3 and BLIP-2 to play Dixit and gathered some friends and co-workers to play against it.

Deep Metric Learning: a (Long) Survey

A brief survey of common supervised approaches for Deep Metric Learning, as well as the new methods proposed in recent years.

How to Dominate on Tech Interviews

Do you want to dominate your interviewer? Wanna bring him to his knees? Make him think that you’re superior? I’ll tell you how!

Guide to "Instant Noodles" in Multi-Task Learning

An in-depth survey on Multi-Task Learning techniques that works like a charm as-is right from the box and are easy to implement – just like instant noodle!

Remarks on 14th Smale's Problem

The connection between the proof of the existance of the Lorenz Attractor, its Geometric Flow Model, and the Knot Theory Model.