With the application and development of digital technology of landscape architecture, big data technology and artificial intelligence technology have been gradually applied to landscape architecture, which have solved many problems. Machine learning technology, as a tool for processing big data and one of the core technologies of artificial intelligence, has gradually become a hot topic in landscape architecture research. In this paper, the relevant practices at home and abroad in recent years have been systematically summarized and analyzed. Firstly, the application background was introduced to analyze the applicability of machine learning in landscape architecture. Secondly, based on different perspectives for machine learning to solve the problem in the fields of landscape architecture, the existing methods and processes of experiments at home and abroad were analyzed with examples from the site information extraction, landscape analysis and evaluation, self-generating system for planning schemes based on the deep learning algorithm. Finally, based on the analysis of relationship between different fields and application in the same field of machine learning technology in landscape architecture, the future trend was prospected. From the technical level, constructing a comprehensive landscape evaluation model and landscpae analysis model based on a variety of data is a promising research direction in the future. On the application level, constructing digital planning and design methods based on various artificial intelligence methods with the integration of various intelligent technologies, the integration of multi-source data and the combination of practical planning and design projects is an important trend of machine learning in the future.