Data Science Project Quick-Start

Eugene Yan · 4 years ago

A data scientist describes best practices for starting machine learning projects, emphasizing understanding business intent and constraints before building models. Key concrete practices include defining success metrics before development, conducting rapid baseline experiments within one to two days, and automating experiment pipelines using tools like Hyperopt and MLFlow. The approach shifts focus from immediately training models to carefully scoping the problem, exploring data quality issues, and setting realistic targets based on feasibility rather than wishful thinking.