Beyond Real-World Limitations: Synthetic Data Generation for Improved ML Perf

Abstract:
In this presentation, we tackle one of the most pressing challenges in applied AI: creating accurate, customized models for scenarios with limited data. Our approach combines the generative capabilities of large language models with the flexibility of AI agents to produce and validate synthetic, domain-specific training data. We'll explore how this method overcomes the limitations of traditional autoML solutions and the prohibitive costs of custom LLMs. We'll demonstrate how our solution dramatically improves model performance, even in scenarios with initially sparse datasets. Let’s be there to discover how this method could apply to your work.

You can watch it online here:
https://fb.me/e/8YOTg4Zut
*Stream starts at 17:45

Program:
17:30 Welcome chat
18:00 Talk
18:50 Discussion
19:10 Networking (Impact Hub)

About MLMUs:
Machine Learning Meetups (MLMU) is an independent platform for people interested in Machine Learning, Information Retrieval, Natural Language Processing, Computer Vision, Pattern Recognition, Data Journalism, Artificial Intelligence, Agent Systems and all the related topics. MLMU is a regular community meeting usually consisting of a talk, a discussion and subsequent networking. Except of Prague, MLMU also spread to Brno, Bratislava and Košice.