Transactional Machine Learning with Data Streams and AutoML (PDF)
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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.
Thisbook 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 TML will evolve in the future, and the growing need by organizations for deeper insights from data streams.
By the end of the book, you will have a solid understanding of TML. You will know how to build TML solutions with all the necessary details, and all the resources at your fingertips.You will:
- Discover transactional machine learning
- Measure the business value of TML
- Choose TML use cases
- Design technical architecture of TML solutions with Apache Kafka
- Work with the technologies used to build TML solutions
- Build transactional machine learning solutions with hands-on code together with Apache Kafka in the cloud
Sebastian is also a published author with seven publications in international peer-reviewed journals and books. One of his publications (International Journal of Engineering Education, 2004) was cited as landmark work in the area of online testing technology. He also developed the world's first Apache Kafka connector for transactional machine learning: MAADS-VIPER.
Dr. Maurice received his PhD in electrical and computer engineering from the University of Calgary, and has a master's in electrical engineering, and a master's in agricultural economics, with bachelors in pure mathematics and bachelors (hon) in economics.
Dr. Maurice also teaches a course on data science at the University of Toronto and actively helps to develop AI course content at the University of Toronto. He is also active in the AI community and an avid blogger and speaker. He also sits on the AI advisory board at McMaster University.
- Autor: Sebastian Maurice
- 2021, 1st ed, 276 Seiten, Englisch
- Verlag: APress
- ISBN-10: 1484270231
- ISBN-13: 9781484270233
- Erscheinungsdatum: 19.05.2021
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 4.75 MB
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