[Special thank you to Ian Kivlichan for many useful pointers (E.g. the 100+ year old Nature paper “Vox populi”) and nice feedback. 🙏 ] High-quality data is the fuel for modern data deep learning model training. Most of the task-specific labeled data comes from human annotation, such as classification task or RLHF labeling (which can be constructed as classification format) for LLM alignment training. Lots of ML techniques in the post can help with data quality, but fundamentally human data collection involves attention to details and careful execution.
labeling
Python library for computer vision labeling tasks. The core functionality is to translate bounding box annotations between different formats-for example, from coco to yolo. - GitHub - pylabel-proj...
If an AI model can make decisions on the company’s behalf through products and services, that model is essentially their competitive edge.
In this article, I will present a tutorial on how to add labels to a dataset for sentiment analysis using Python. Adding labels to a dataset.
How does Semi-Supervised Machine Learning work, and how to use it in Python?
One of the best labelling tools I have ever used.
Learn about different types of annotations, annotation formats and annotation tools
How to use snorkel’s multi-class implementation to create multi-labels
157 votes, 15 comments. Hi, Reddit. I'm excited to share confident learning for characterizing, finding, and learning with label errors in datasets…