ML and data science teams often spend a disproportionate amount of their time processing, labeling, and augmenting training data. A training data platform brings together all the people, processes, and data involved in creating and improving training data in an efficient pipeline that saves both time and costs.
Read this guide to discover a smarter, easier approach to creating and managing high-quality training data, along with tried-and-true best practices, tools, and workflows that leading AI teams can use to annotate data, collaborate, automate parts of the labeling process, and build an optimized data engine.
How a training data platform improves labeling productivity
Use cases and common features of a training data platform
Who can benefit most from a training data platform at your organization
The ROI of using a training data platform