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Can I read Transactional Machine Learning with Data Streams and AutoML : Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python on EtoBox?
Transactional Machine Learning with Data Streams and AutoML : Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python by Sebastian Maurice; Safari, an O'Reilly Media Company is a nonfiction available to read on EtoBox.
What is Transactional Machine Learning with Data Streams and AutoML : Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python about?
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, algorithms, and users of the insights). This book will strengthen your knowledge of the inner workings of TML solutions using data streams with auto machine learning integrated with Apache Kafka. Transactional Machine Learning with Data Streams and AutoML introduces the industry challenges with applying machine learning to data streams. You will learn the framework that will help you in choosing business problems that are best suited for TML. You will also see how to measure the business value of TML solutions. You will then learn the technical components of TML solutions, including the reference and technical architecture of a TML solution. This book also presents a TML solution template that will make it easy for you to quickly start building your own TML solutions. Specifically, you are given access to a TML Python library and integration technologies for download. You will also learn how
Who reads Transactional Machine Learning with Data Streams and AutoML : Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Sebastian Maurice; Safari, an O'Reilly Media Company
- Publisher
- Apress : Imprint: Apress
- Published
- 2023
- Language
- EN
- ISBN
- 9781484270233
- Category
- nonfiction
- Subjects
- Mathematics, Language Learning, Computer Science
Other editions & translations
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