Training with Multiple Workers using TensorFlow Quantum

Posted by Cheng Xing and Michael Broughton, Google Training large machine learning models is a core ability for TensorFlow. Over the years, scale has become an important feature in many modern machine learning systems for NLP, image recognition, drug discovery etc. Making use of multiple machines to boost computational power and throughput has led to great advances in the field. Training large machine learning models is a core ability for TensorFlow. Over the years, scale has become an important feature in many modern machine learning systems for NLP, image recognition, drug discovery etc. Making use of multiple machines to boost computational power and throughput has led to great advances in the field. In this tutorial you will walk through how to use TensorFlow and TensorFlow quantum to conduct large scale and distributed QML simulations.