How to build a machine learning model in 7 steps
Organizations are implementing AI projects for numerous applications in a wide range of industries. But building a viable, reliable and agile machine learning model that streamlines operations and bolsters business planning takes patience, preparation and perseverance.
The right machine learning approach and methodologies stem from data-centric needs and result in projects that focus on working through the stages of data discovery, cleansing, training, model building and iteration. In this e-guide, we take a look into the main steps for building an efficient machine learning model.