The first segment was a deep dive into understanding the new business imperative of today’s ML world.
Our Consulting expert, Ramyasree Devarakonda, initiated the conversation by examining the way data labeling and augmentation have become the true bottleneck in AI/ ML projects. This step is indeed eating up most of the time, budget, and effort.
She highlighted some of the practical problems, including the ambiguity in the labeling process, the importance of hierarchy (particularly the element of context setting, and how different it will be for every project), the lack of collaboration between different teams, and so on.
Paying heed to the challenges faced by enterprises, Dheeraj steps in during the next segment, to unveil an enterprise-grade technology solution that not only uses state-of-the-art active learning techniques to deliver labeling that is faster, easier, and more accurate, but also addresses the labeling complexities of today. This solution is packed with all the features, framework support, models, and workflows to truly blaze a way out of the current-day ML problems. Curious to know more about Zaastra? Click here.
Up next, in the third Segment, it was Raju’s turn to walk us through the world of active learning – the why, what, and how dimensions of it. He sprinkled some tough geeky ML on us, including the concept of Empirical Risk Minimization (ERM), Vapnik-Chervonenkis (VC) Theory, and Disagreement based Active Learning.
These concepts were developed further by Akhil, with a detailed explanation of the most commonly used active learning strategies and the challenges faced by teams in adopting them.
Following a brief Q&A session, Srinivas Atreya revisited some of the conventional wisdom in deep learning. He dug deeper into why disagreement-based learning does not work in the deep neural network world. He highlighted some of the interesting developments in this area that will evolve rapidly over the next few years.
We are thankful for all the wonderful and constructive feedback received on the event. We will keep them in mind for the next one. However, we are thrilled that the most common refrain was