Improving Machine Learning Outcomes

In order to build successful machine learning solutions, there are certain fundamental ideas that everyone involved needs to understand. In this blog post, we look at three key early stages of the design process that managers can focus on to ensure that the project is headed toward a successful outcome. This post presumes the reader already understands distinctions in machine learning such as supervised and unsupervised models, training and testing stages, and the overall machine learning lifecycle. Returning to the earliest stage of defining the business problem, we focus our attention on three key objectives. Each of these objectives are introduced to some extent in data science training.