Quantum Machine Learning (QML) has emerged as a transformative field, combining the power of quantum computing and machine learning to tackle complex problems across various domains. In recent years, QML has gained significant traction in the realm of quantum chemistry, offering promising solutions to age-old challenges faced by chemists and researchers. In this blog, we will explore how Quantum Machine Learning is revolutionizing quantum chemistry, the key concepts behind it, and the potential impact on the future of chemical research. Understanding Quantum Machine Learning: To grasp the potential of Quantum Machine Learning for Quantum Chemistry, let's first understand the foundations of QML. Traditional machine learning algorithms operate on classical computers, processing and analyzing vast datasets to make predictions and classifications. However, quantum machine learning algorithms harness the principles of quantum mechanics to encode and process information more efficiently.
In this blog, I will share my academic and research journey.