Transactional machine learning with data streams and AutoML : build frictionless and elastic machine learning solutions with Apache Kafka in the cloud using Python /

Understand how to apply auto machine learning to data streams and create transactional machine learning (TML) solutions that are frictionless (require minimal to no human intervention) and elastic (machine learning solutions that can scale up or down by controlling the number of data streams, algori...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Maurice, Sebastian (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Berkeley] : Apress, [2021]
Temas:
Apache Kafka (Electronic resource)
Machine learning.
Python (Computer program language)
Apprentissage automatique.
Python (Langage de programmation)
Machine learning
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Chapter 1: Introduction: Big data, Auto Machine Learning and Data Streams
  • Chapter 2: Transactional Machine Learning
  • Chapter 3: Industry Challenges with Data Streams and AutoML
  • Chapter 4: The Business Value of Transactional Machine Learning
  • Chapter 5: The Technical Components and Architecture for Transactional Machine Learning
  • Overview of a TML Solution
  • Chapter 6: Template for Transactional Machine Learning Solutions
  • CHAPTER 7: Visualize Your TML Model Insights: Optimization, Predictions and Anomalies
  • Chapter 8: Evolution and Opportunities For Transactional Machine Learning in Almost Every Industry
  • Chapter 9: Conclusion and Final Thoughts.

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