This talk will discuss technical challenges and recent results related to deep learning/machine learning in 6G network optimization. The talk is mainly divided into four parts. In the first part, this talk will introduce 6G, deep learning, and machine learning, discuss the 6G mobile network architecture, and provide some main technical challenges of deep learning/machine learning in 6G network optimization. In the second part, this talk will focus on the issue of deep learning/machine learning in 6G network optimization and provide different recent research findings that help us to develop engineering insights. In the third part, this talk will address the resource allocation and MAC layer design of deep learning/machine learning in 6G network optimization and address some key research problems. In the last part, this talk will summarize by providing a future outlook of deep learning/machine learning in 6G network optimization