machine-learning

A detailed guide on how to build applications with foundation models.

Ordinal regression has order structure between classes and there are dedicated loss functions to use this information.

Reflecting on 2024's deep learning breakthroughs! Discover my top 10 favorite research papers that shaped the field this year.

RLHF is not the only method for AI alignment. This article introduces modern algorithms like DPO and KTO that offer simpler and more stable alternatives.

Let's look back at the significant progress made in deep learning in 2023! Here are my 10 favorite papers.

Uncover the top deep learning advancements of 2022. A year-in-review of key research papers and applications.

Let's look back at the updates in deep learning in 2021! This post covers four application projects worth checking out

Let's look back at the updates in deep learning in 2021! This post covers eight research papers worth checking out.

Let's re-inplement face swapping in 10 minutes! This post shows a naive solution using a pre-trained CNN and OpenCV.

NeurIPS 2020 virtual conference was full of exciting presentations! Here I list some notable ones with brief introductions.

Let's look back on the machine learning papers published in 2020! This post covers 10 representative papers that I found interesting and worth reading.

If you want to use a custom loss function with a modern GBDT model, you'll need the first- and second-order derivatives. This post shows how to implement them, using LightGBM as an example

This post compares the behaviors of different feature importance measures in tricky situations.