Transactional Machine Learning with Data Streams and AutoML: Build Frictionless and Elastic Machine Learning Solutions with Apache Kafka in the Cloud Using Python

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2021

S. MauriceTransactional Machine Learning with Data Streams and AutoMLhttps://doi.org/10.1007/978-1-4842-7023-3_8

8. Evolution and Opportunities for Transactional Machine Learning in Almost Every Industry

Sebastian Maurice¹  

(1)

Toronto, ON, Canada

 

We have discussed several areas that make TML effective in the application of AutoML to data streams for greater business insights and impact. What underlies TML opportunities is the belief that fast data will require fast machine learning for fast decision-making. Given that fast data is here to stay and will only grow in pervasiveness, it presents an opportunity for organizations to harness it and use it to add ...