Machine Learning Methods for option pricing & model calibration

The aim of this article is to present the application of machine learning and deep learning to option pricing and financial model calibeation in a data-driven apporach. Efficient numerical computation has become increasingly important in finance with real-time risk management or counterparty credit risk; The motivation to use machine learning methods is to save computational cost in comparison with classical numerical metods such as Monte-Carlo, numerical integreation ot root-finding without loss of precision.