1 Introduction  
2 Background of ML Methods  
3 GNSS Signal Analysis and Classification  
4 Environmental Context and Scenario Recognition  
5 Anomaly Detection and Quality Assessment  
6 GNSS Integration with Other Sensors  
7 Prediction and Forecasting  
8 Position Error Modeling/Accuracy Enhancement  
9 Other Use Cases  
10 Limitations of Discussed Methods and Potential Solutions  
11 Promising Opportunities  
12 Conclusion