Tutorials

Active Learning: Speed up training data cycles with uncertainty sampling

Machine learning engineers often rely on an active learning framework to surface the most informative data to learn from.

3 months ago • 10 min read

labeling

Case study: image labeling with JavaScript

This post will describe how to design a system for labeling objects on an image by a human. I will show you how to use React, 2d canvas and Konva framework to make an app that allows you to highlight objects. Also, I will cover some edge cases specific to that task.

8 months ago • 5 min read

Tutorials

Model Predictions, Semi-Automatic Labeling and Quality Assurance in Production

Model predictions play two vital roles in a machine learning pipeline. Predictions can be used to accelerate labeling speed as well as test and improve the accuracy of production models.

a year ago • 6 min read

Tutorials

How to Measure Quality when Training Machine Learning Models

With quality assurance processes data scientists can monitor overall consistency and accuracy of training data, quickly troubleshoot quality errors, improve instructions, on-boarding, and training of labelers, and better understand the project specifics on what and how to label.

2 years ago • 7 min read

Case Studies

How to Scale Training Data

A Guide to Outsourcing Without Compromising Data QualityIn order for data science teams to outsource annotation to a managed workforce provider — also known as a Business Process Outsourcer (BPO) — they must first have the tools and infrastructure to store and manage their training data. Data management tools and infrastructure should

2 years ago • 7 min read

Labelbox July Updates

The new Editor is a step forward for scaling production AI

Stanford CS230 grad students research the next generation of AI-driven land urban air vehicles

Labelbox May updates

Active Learning: Speed up training data cycles with uncertainty sampling

Case study: image labeling with JavaScript

Model Predictions, Semi-Automatic Labeling and Quality Assurance in Production

How to Measure Quality when Training Machine Learning Models

How to Scale Training Data