Whether we stream our favorite series, develop new drugs or have us being chauffeured by a self-driving car -- machine learning is an essential part of our modern life, and of our future. But the growing amount of data and our increasing demands pose difficulties for today's classical computers. Can quantum computing overcome these challenges? What potentials does the emerging field of quantum machine learning have?
Machine Learning has revolutionized our lives: image classification, natural language processing, drug discovery, weather forecasting, predictive maintenance, etc. The list of applications grows continuously. All of these models rely on the availability of powerful computers. In fact, over the past decades the computational resources of one chip have doubled every year. Currently, however, we are approaching the physical limitations of what classical computers can achieve. Yet our resource requirements keep increasing! Research institutes and industry are, thus, looking into alternative computing models such as quantum computing. With this emerging technology we may be able to push computational applications even further and tackle new challenges that are currently out of reach for existing classical processors.
In this course, I not only learn about quantum machine learning and its prospects, but also how to solve concrete tasks with both classical and quantum models.