From 100,000 to Under 500 Labels: How Google AI Cuts LLM Training Data by Orders of Magnitude
Google’s active learning method fine-tunes LLMs with 10,000x less data using high-fidelity expert-labeled examples
labeling
Thinking about High-Quality Human Data | Lil'Log
[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…
pylabel-project/pylabel: Python library for computer vision labeling tasks. The core functionality is to translate bounding box annotations…
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...
Why fast, effective data labeling has become a competitive advantage (VB Li
If an AI model can make decisions on the company’s behalf through products and services, that model is essentially their competitive edge.
Add Labels to a Dataset for Sentiment Analysis
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.
Semi-Supervised Learning — How to Assign Labels with Label Propagation Algo
How does Semi-Supervised Machine Learning work, and how to use it in Python?
A Free And Powerful Labelling Tool Every Data Scientist Should Know
One of the best labelling tools I have ever used.
Theoretical Understandings of Product Embedding for E-commerce Machine Lear
Layered Label Propagation Algorithm
An algorithm for community finding
Image Data Labelling and Annotation — Everything you need to know
Learn about different types of annotations, annotation formats and annotation tools
Using Snorkel For Multi-Label Annotation.
How to use snorkel’s multi-class implementation to create multi-labels
How to Label 1M Data Points per Week
[R] Announcing Confident Learning: Finding and Learning with Label Errors i
157 votes, 15 comments. Hi, Reddit. I'm excited to share confident learning for characterizing, finding, and learning with label errors in datasets…
Using LLMs for Automated Data Categorization in Google Sheets
This post unveils a well-kept secret unknown to many: using externally hosted Large Language Models (LLMs) in Google Sheets to perform NLP tasks on text
By default, the script uses the "facebook/bart-large-mnli", a BART model trained for multi-class text classification
paste the token in your script, replacing the ‘ <YOUR HUGGINGFACE API KEY> ‘ part with your token, save the script, and go back to Google Sheets to start playing!