10 training data practices used by the most successful AI teams
Machine learning teams today are confronted by a variety of challenges around the development of training data, such as building an efficient and optimized labeling pipeline, improving the quality of labeled data, incorporating advanced methodologies such as automation, and more.
At Labelbox, we’ve partnered with hundreds of leading AI teams across industries to develop solutions to these challenges. In this ebook, you’ll discover:
- Common roadblocks faced by AI teams
- The collaborative workflows used by highly successful ML teams
- Processes, standards, and tools that enable the creation of high-quality training data and AI breakthroughs
- How teams can prepare for and address unexpected issues such as edge cases