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    Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics Rich Collier, Bahaaldine Azarmi

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics Rich Collier, Bahaaldine Azarmi - okladka książki

    Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics Rich Collier, Bahaaldine Azarmi - okladka książki

    Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics Rich Collier, Bahaaldine Azarmi - audiobook MP3

    Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics Rich Collier, Bahaaldine Azarmi - audiobook CD

    Autorzy:
    Rich Collier, Bahaaldine Azarmi
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    304
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data.
    As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure.
    By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly.

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    O autorach książki

    Rich Collier is a solutions architect at Elastic. Joining the Elastic team from the Prelert acquisition, Rich has over 20 years' experience as a solutions architect and pre-sales systems engineer for software, hardware, and service-based solutions. Rich's 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.
    Bahaaldine Azarmi, or Baha for short, is the head of solutions architecture in the EMEA South region at Elastic. Prior to this position, Baha co-founded ReachFive, a marketing data platform focused on user behavior and social analytics. He has also worked for a number of different software vendors, including Talend and Oracle, where he held positions as a solutions architect and architect. Prior to Machine Learning with the Elastic Stack, Baha authored books including Learning Kibana 5.0, Scalable Big Data Architecture, and Talend for Big Data. He is based in Paris and holds an MSc in computer science from Polytech'Paris.

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