Seize Machine Learning With The Elastic Stack Chronicled By Bahaaldine Azarmi Format Kindle

Features Get actionable insights from your Elasticsearch data with the help of this handy guide Sift through the large volumes of data and combine the power of machine learning with the search and analytics capabilities of the Elastic stack Get a significant performance and operational advantage by integrating your Elastic stack with external data science tools Book Description

The open source loganalysis stack now has machine learning components for more sophisticated analytics, albeit through a commercial addon.

The book will start with understanding how to install and set up the Xpack package, you will see how you can perform timeseries analysis on varied kinds of data such as log files, network flows, application metrics and financial data.
You will learn how to deploy machine learning within the Elastic Stack for logging, security and metrics, Moving on, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster, and made resilient to failure, You will also see how you can integrate different thirdparty data science tools with the Elastic stack to get the most efficient insights from your data.
Finally, you will also understand the performance aspects of incorporating machine learning within the Elastic ecosystem, and see how you can create anomaly detection jobs and view results right from Kibana.

What you will learn Install Elastic stack to use Elastic ML Learn how Elastic ML has been used to detect critical business anomalies, Create jobs to reveal anomalies Explore security analytics with Elastic ML Understand multidimension analysis and profile entities Use Elastic ML result to do forensic analysis in Elastic Graph About the Author

Bahaaldine Azarmi, Baha in short, is a Solutions Architect at Elastic.
Prior to this position, Baha cofounded reachfive, a marketing dataplatform focused on user behavior and

social analytics, Baha also worked for different software vendors such as Talend or Oracle, where he held a Solutions Architect or Architect position, Before Elastic Machine Learning, Baha authored books such as Learning Kibana,, Scalable Big Data Architecture or Talend for Big Data, Baha is based in Paris and has a Master's Degree in computer science from Polytech'Paris,

Rich Collier Solutions Architect, Elastic, Joining the Elastic team from the Prelert acquisition, Rich has overyears experience as a Solutions Architect / PreSales Systems Engineer for software, hardware, and servicebased solutions.
Richs technical specialties include: Big data analytics, Machine learning, Anomaly detection, Threat detection, Security Operations, Application Performance Management, Web Applications, and Contact Center Technologies, Rich is based in Boston, Massachusetts

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