Train, evaluate, monitor, infer: End-to-end machine learning in Elastic

Machine learning pipelines have evolved tremendously in the past several years. With a wide variety of tools and frameworks out there to simplify building, training, and deployment, the turnaround time on machine learning model development has improved drastically. However, even with all these simplifications, there is still a steep learning curve associated with a lot of these tools. In order to use machine learning in the Elastic Stack, all you really need is for your data to be stored in Elasticsearch. Once there, extracting valuable insights from your data is as simple as clicking a few buttons in Kibana.