Machine learning can be effectively applied to nginx log data to extract operational insights and identify website issues using Elastic's X-Pack Machine Learning tools. The blog post describes how specific machine learning configurations, such as "Single Metric Job" and "Multiple Metric Job" wizards, can simplify the process of anomaly detection and analysis of web traffic. By analyzing data from nginx logs, users can detect significant anomalies in visitor rates, HTTP status code changes, and unusual client behaviors, such as those from bots or attackers. The post highlights a notable example on February 27th, where anomalies were detected in both overall event rates and unique visitor counts, which were attributed to a configuration change causing operational issues. These insights can be leveraged for early detection and alerting, providing operations teams with timely information to address system behavior changes. Future Elastic Stack releases will offer pre-packaged configurations to simplify the deployment and extend the usefulness of these tools for end users.