- eBook:Transactional Machine Learning with Data Streams and AutoML: Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python
- Author:Sebastian Maurice
- Edition:1 edition
- Data:June 19, 2021
- Pages:291 pages
- Format:PDF, ePUB
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 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.
What You Will Learn
- 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
Data scientists, machine learning engineers and architects, and AI and machine learning business leaders.
Chapter 2: Transactional Machine Learning
Chapter 3: Overcoming Challenges to ML Adoption
Chapter 4: The Business Value of Transactional Machine Learning
Chapter 5: The Technical Components and Architecture for Transactional Machine Learning Solutions
Chapter 6: Transactional Machine Learning Solution Template with Streaming Visualization
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: TML Project Planning Approach and Closing Thoughts