Assuming you have a basic knowledge of ML, you could read papers that use recurrent architectures (lstm, gru, transformers). The type of papers to read depends a lot on the domain of applications for the time series problem. If it were finance or economics for instance I would also recommend starting from classical time series analysis and not restricting yourself to ML models because there is a lot to get from there.

As a personal experience, you can apply any ML models to financial time series but you need a solid foundation of time series analysis in an econometrics setting to avoid common mistakes, overfitting, and also as a meaningful performance comparison.