AUTHOR

Articles by Tom Grabowski

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Using AIOps for automation and efficiency in observability and IT operations

Common use cases and scenarios for a successful AIOps deployment within observability. From monitoring to anomaly detection and root cause analysis, understand how you can improve your AIOps deployment and see success.

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Introduction to modern natural language processing with PyTorch in Elasticsearch

In 8.0, you can now upload PyTorch machine learning models into Elasticsearch to provide modern natural language processing (NLP). Integrate one of the most popular formats for building NLP models and incorporate them as part of a NLP data pipeline.

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Detecting rare and unusual processes with Elastic machine learning

To secure your environment, Elastic Security has many out-of-the-box machine learning configurations for detecting rare activity, networks, and processes, as well as tools to customize your own anomaly detection jobs.

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Using Elastic machine learning rare analysis to hunt for the unusual

Learn how Elastic machine learning can be used to easily build a model of your data and apply anomaly detection algorithms to detect what is rare/unusual in the data.

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Designing for Change in Elastic Machine Learning

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Introducing data visualization and modules in machine learning

Walk through new features for making it easier to create useful machine learning jobs in 6.1 with the new Data Visualizer and modules.

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On-demand forecasting with machine learning in Elasticsearch

The newest X-Pack feature in 6.1 is on-demand forecasting. Machine learning can model the data and predict multiple time intervals into the future.

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Sizing for Machine Learning with Elasticsearch

The sizing of hardware and cluster for machine learning depends on the use-case. We can guide you through best practices to use for your ML needs.

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Using Elasticsearch and Machine Learning for IT Operations

An introduction to how IT Operations can take advantage of Elastic's machine learning.