In the field of quantum computing, there still remains a gap between the theory and practical implementation for most algorithms. This gap lies in the number of measurements required to achieve a high-quality result. I am interested in methods to reduce this requirement on the number of measurements. My project demonstrated the potential for certain classical machine learning algorithms to reduce the measurement requirements by orders of magnitude. This work will be key step to realizing the full potential of quantum computers.