Debugging
5 ML Mistakes I Made So You Don't Have To
··2135 words·11 mins
AI/ML
Tutorials
Machine-Learning
Best-Practices
Lessons-Learned
Debugging
Abstract
This post is a checklist of failure modes that quietly ruin ML projects: bad data inspection, leakage, weak evaluation, class imbalance, and irreproducible experiments. The point is not to be dramatic about mistakes, but to make the debugging habits explicit before they cost days of work.