Title:  Advances in Quantum Machine Learning

Abstract: Quantum machine learning represents a convergence of quantum computing and classical machine learning, opening new avenues for algorithmic innovation. In this talk, I will discuss recent developments in quantum algorithms designed for tasks such as classification, regression, clustering, and dimensionality reduction. By integrating quantum resources with neural network architectures, the goal is to overcome computational challenges inherent in classical methods and explore potential performance enhancements. I will highlight key breakthroughs, practical implications, and promising future directions in this rapidly evolving field.