A short video on using a machine learning deep neural network to predict the failure of oil production equipment with enough lead time to ship new equipment to site before the old equipment breaks.
This workshop uses TinkerPop Gremlin, and a handful of sample data sets, to teach the Gremlin traversal language through hands-on examples.
Digital Twins are the next logical step in an IoT implementation. Data storage for a digital twin can include a property graph database such as JanusGraph or DSE Graph, a time series database like TimescaleDB, and an analytical database like Redshift, Google Bigquery, or HP Vertica.
Using unsupervised machine learning, we relate documents together based on their content. This analysis operates directly on the text in the documents, building up clusters of similar context so that an analyst, or another algorithm, can investigate all of their company's data on a single subject.
