On July 23, 2020 at 9 am PT (noon ET), Arshak Navruzyan, CEO, CTO and co-founder of platform.ai, and Jonathan Epstein, the company’s COO, will co-present the free half-hour webinar “AI Training Data Image Labeling and Few-Shot Learning: Under the Hood with Platform.ai,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page:
The time it takes to accurately and comprehensively label training images remains one of the biggest problems in AI. Outsourcing the labeling effort is particularly ineffective in cases where subject matter expertise is necessary to label the images or the images are confidential. Label accuracy in cases involving small training sets also remains a challenge.
In this online presentation, platform.ai will discuss how the company employs a diversity of AI techniques to visualize image sets, facilitating mass expert labeling, as well as how it applies new few-shot learning approaches to solve for low-data cases. Demonstrations of the company’s products in action will reinforce and expand on these concepts. And a 15-minute question-and-answer session will follow the presentation.
By attending this session, you’ll gain and learn:
- Ways to accelerate labeling and training
- Insights on dimensionality reduction techniques
- Insights on few-shot learning techniques
- Ways to handle out-of-domain image predictions
Arshak Navruzyan is CEO and co-founder of platform.ai, which accelerates the path to computer vision, as well as CEO and founder of launchpad.ai, one of the world’s preeminent AI consulting and training companies. Passionate about expanding the community of machine learning specialists and the spread of machine learning applied to high-value problems, Arshak launched both companies to address the critical shortage of AI specialists worldwide. Platform.ai enables subject matter experts to develop their own computer vision without coding.
To register for this free webinar, please see the event page. For more information, please email [email protected].
