Unlocking Reliable Machine Learning: Conformal Prediction by Valery Manokhin — ShareChat ML Seminar

The ShareChat Machine Learning Seminar invites world-leading researchers to present recent advances in their work in all areas related to machine learning and the problems we solve at ShareChat. Abstract: In an era where the accuracy of machine learning models is paramount, how do we ensure our predictions are not just accurate but reliable? Join us as we delve into the world of Conformal Prediction, a cutting-edge approach to producing quantified, confidence-driven predictions. This talk will unpack the foundational principles of Conformal Prediction, showcase its real-world applicability, and explore its transformative potential for businesses looking to harness the power of dependable AI. Whether you're an AI enthusiast or a professional aiming to bolster internal machine learning capabilities, this session offers an insightful journey into the next frontier of trustworthy predictive analytics. Watch, learn, and be part of the paradigm shift towards more accountable and transparent AI predictions. Short Bio: Valeriy Manokhin is the creator of Awesome Conformal Prediction, a learning resource that has over 2.7k stars. He holds multiple degrees, including a PhD in ML specializing in probabilistic and conformal prediction. His work has been cited by over 210 papers, and he is the author of the book called "Practical Guide to Applied Conformal Prediction: Learn and apply the best uncertainty frameworks to your industry applications".