Stages to Machine Learning

This article outlines a structured approach to machine learning projects, emphasizing the importance of starting with a clear business metric and involving management to define specific, measurable goals. It then covers stages such as blending data from multiple sources, exploring and profiling data to understand its quality, cleaning messy data, and transforming variables for consistency. The content is practical and focused on the technical workflow of machine learning, making it relevant for IT and technology professionals working on data science projects.