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

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
Otros Autores: Maurice, Sebastian, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: [Place of publication not identified] : Apress [2021]
Edición:1st ed. 2021.
Materias:
Machine learning.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631729506719
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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