Guides

An introduction to model metrics

Learn how you can use model metrics to surface low-performing classes, find and fix labeling errors, and improve the overall performance of the model before it hits production on real-world data.

Using Labelbox and Weights & Biases to fine tune your computer vision projects

Learn how you can use Labelbox and Weights & Biases together to build better computer vision models. Follow a step-by-step workflow of data curation, annotation, model diagnostics and hyperparameter tuning.

How to get started in Labelbox Model: Train, evaluate, and improve your ML models

Learn how to ship better models faster by leveraging Labelbox Model. In this guide, we'll walk you through a COCO object detection example to get you onboarded in Model with your first project, model, and model run.

How to kickstart and scale your data labeling efforts

Learn how to effectively kickstart and scale your data labeling efforts to reduce cost, while maintaining the desired quality required for your use case.

How to evaluate and optimize your data labeling project's results

Learn how to evaluate the results of your labeling project in order to further optimize and improve future iterations and batches of data.

How to create a quality strategy for your data labeling project

Learn how to create a quality strategy to ensure your project is producing valuable, high-quality training data for your use case.

How to define your data labeling project's success criteria

Learn how to effectively define your labeling project's success criteria so all tasks lead to consistent output with high quality.

How to define a task for your data labeling project

Learn how to align on key components of your project: define a task, create an ontology, and determine timelines for your labeling project.

How to find similar data in one click

Powerful similarity search capabilities can give your team an edge by helping find specific data points in an ocean of data. Learn more about how to find similar data in one click with Labelbox.

How to train a chatbot

The rise in natural language processing (NLP) language models have given machine learning (ML) teams the opportunity to build custom, tailored experiences for their customers. Learn how to train a domain-specific chatbot.