Developing AI-integrated machine learning models, in reasonable likelihood, is a great deal of data & data science that goes into sourcing the suitable datasets for AI development — and then — preparing the correct training data for machine learning models for a successful computer vision program. The data fed into the platforms and machines work in integration with AI algorithms and computer vision setup to power up process automation. These intrinsically interlinked mechanisms enable the machine learning system to make accurate predictions or do things on its own with minimal or entirely no human intervention.

This ebook is very much inclined to clarify the concepts of data annotation and data labeling, i.e., the essential prerequisites in the course of AI integration into machine learning models. The end purpose of the book is to provide you with an insight into the significance of data and data-inclined processes, e.g., data annotation and data labeling — that propel the path to the development of quality training data for AI and machine learning models.