Tutorials

Automation

John Thomas | 6 months ago | 3 min read

Tutorial: Use model-assisted labeling to improve speed and accuracy

Follow this tutorial to learn how model-assisted labeling can improve labeling speed and accuracy using your own model.

Tutorials

Randall Lin | a year ago | 10 min read

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.

labeling

Labelbox | a year ago | 5 min read

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.

Tutorials

Labelbox | 2 years ago | 6 min read

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.

Tutorials

Labelbox | 2 years ago | 7 min read

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.

Case Studies

Labelbox | 2 years ago | 7 min read

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

Labelboxer Spotlight: Nikki Gantos, Engineer

Ontology management with Labelbox

How enterprises can combat climate change with ML

How Sharper Shape built a robust ML pipeline with Labelbox and Valohai

Tutorial: Use model-assisted labeling to improve speed and accuracy

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