dcai-lab

# Lab assignments for Introduction to Data-Centric AI

This repository contains the lab assignments for the [Introduction to
Data-Centric AI](https://dcai.csail.mit.edu/) class.

Contributions are most welcome! If you have ideas for improving the labs,
please open an issue or submit a pull request.

If you're looking for the 2023 version of the labs, check out the [2023
branch](https://github.com/dcai-course/dcai-lab/tree/2023).

## [Lab 1: Data-Centric AI vs. Model-Centric AI][lab-1]

The [first lab assignment][lab-1] walks you through an ML task of building a
text classifier, and illustrates the power (and often simplicity) of
data-centric approaches.

[lab-1]: data_centric_model_centric/Lab%20-%20Data-Centric%20AI%20vs%20Model-Centric%20AI.ipynb

## [Lab 2: Label Errors][lab-2]

[This lab][lab-2] guides you through writing your own implementation of
automatic label error identification using Confident Learning, the technique
taught in [today’s lecture][lec-2].

[lab-2]: label_errors