Garbage In Garbage Out

Definitions

1. The principle that bad input leads to bad output, no matter how impressive the system processing it may be. It applies equally to analytics, software pipelines, and machine learning.

   In plain English: Bad input data leads to bad results.

   Example: "The model isn't the main issue here; it's still garbage in garbage out."

Related Terms

• Epoch
• Inference
• Few-Shot Learning
• Synthetic Data
• Megabyte
• Propensity Model
• AI Model
• Data Swamp