dcai-lab and dcai-course
These are **complements** — the lab repository contains hands-on coding assignments that accompany and reinforce the concepts taught in the course repository.
About dcai-lab
dcai-course/dcai-lab
Lab assignments for Introduction to Data-Centric AI, MIT IAP 2024 👩🏽💻
This project provides practical lab assignments to help machine learning practitioners understand and apply data-centric AI techniques. It takes various datasets and models as input, guiding users through improving model performance by focusing on data quality and characteristics, rather than just model architecture. The output is a deeper understanding and practical skills in managing data for better AI outcomes, benefiting data scientists and ML engineers.
About dcai-course
dcai-course/dcai-course
Introduction to Data-Centric AI, MIT IAP 2024 🤖
This course helps you understand and apply Data-Centric AI principles, focusing on improving AI models by systematically enhancing the quality and quantity of your data. You'll go from introductory materials and lab assignments to practical skills in an emerging field. This is for anyone looking to build or deploy more robust and accurate AI systems, including data scientists, machine learning engineers, and AI project managers.
Scores updated daily from GitHub, PyPI, and npm data. How scores work