Machine Learning (ML) has shown great potential in improving the medical imaging workflow. Particularly, in recent years, there has been a significant growth in the use of ML algorithms, especially Deep Learning (DL), for medical image reconstruction. The use of DL-based image reconstruction provides promising opportunities to transform the way cardiovascular MRI is acquired and reconstructed. In this talk, we will introduce recent advances in DL-based reconstruction techniques for cardiac imaging, with emphasis on cardiac MRI reconstruction. We will mainly focus on supervised DL methods for the application and will also discuss about their current limitations, challenges and future opportunities.