In the blog post, Philipp Kahr illustrates how to use Elasticsearch 8.0's custom machine learning capabilities, specifically BERT-based models from Hugging Face, to perform natural language processing (NLP) on text-based datasets. By utilizing CNN articles as a dataset, the process involves extracting location information and plotting it on a map through Kibana's file upload feature, with the help of an Eland client to import machine learning models. The post guides readers through data gathering, model importation, and data adaptation using ingest pipelines and enrich policies to categorize entities like persons and locations. The final step is to visualize the processed data on a dashboard with maps, allowing users to observe the frequency of mentions at different geographic levels, enhanced by a time slider feature to track changes in news coverage over time.