Synthetic Aperture Radar Interferometry (InSAR) technology is a crucial technical means for landslide identification and assessment. Meanwhile, deep learning can accurately identify landslide locations based on landslide-related factors and their positions, and has demonstrated remarkable accuracy in landslide susceptibility evaluation. We introduced the fundamental principles of InSAR and deep learning techniques. It introduces the basic principles of D-InSAR deformation monitoring technology and neural networks. The chapter provides a detailed explanation of the fundamental principles of time-series InSAR deformation monitoring technology, including two classic time-series InSAR deformation monitoring techniques: SBAS-InSAR and PS-InSAR. It also elaborates on three commonly used neural networks: Convolutional Neural Networks (CNN), U-Net networks, and GRU networks.