TML Project Planning Approach and Closing Thoughts
Sebastian Maurice · Apress eBooks · 2021
This book has introduced all aspects of TML, which applies AutoML to data streams integrated with Apache Kafka that allows developers to build TML solutions that are scalable, frictionless, and elastic in the cloud. The importance of frictionless and elasticity is a unique characteristic of TML solutions and a differentiating factor with conventional machine learning (CML). We also formally defined TML along with the five features of TML solutions such as data fluidity, joining data streams, standardization of data streams to JSON, integration of data streams with AutoML, and the ability to create TML solutions with low code. TML is based on the belief that fast data requires fast machine learning for fast decision-making. This does not mean that all fast data needs TML, because if there is no need to make fast decisions, then TML makes little sense.