You can apply high-performance machine learning models to your time series data using Loud ML and InfluxDB, enabling offline predictions with minimal setup. Docker containers are used to create a bridge network for the InfluxDB, Chronograf, and Loud ML services, allowing for easy configuration and deployment. The tutorial covers how to create and train a machine learning model with Loud ML on your InfluxDB database, predict values, and use Chronograf to visualize those predictions. Additionally, it provides an overview of 1-Click Machine Learning, which simplifies the process of creating high-performing models and evaluating them without requiring extensive knowledge of machine learning for time series data.