Optimize your training data pipeline for accuracy and speed
About the Event
Ensuring your training data is labeled with the highest accuracy is the top priority for many ML and CV teams. Over 70% of engineering time is spent on creating and managing training data, rather than developing models. There is no room for low quality training data, yet the business demands you meet release timing commitments.
Discover how you can overcome the accuracy vs speed tradeoff by:
- Adopting highly usable annotation tools that shorten learning curves and delivery cycles
- Creating dynamically adaptable rich workflows that seamlessly pull together disparate stakeholders to label and review data faster
- Freeing up more team time to work on more meaningful and less mundane tasks
What to expect
A live demo of how your team can create custom data workflows to automate and accelerate labeling and AI model development
An introduction to logic and consensus stages - what they are and how they can help you ensure the highest quality of data, faster
Real-life examples of AI-first retail & sports companies, plus food & beverage businesses revolutionizing the space with the use of computer vision
A live Q&A session
We’re leading the era of AI-first software
We help companies build software driven by deep learning, to make it accurate, reliable, and indistinguishable from magic.
