Before You Train the Model: What My First ML Project Taught Me About Data Cleaning

Short summary

A beginner recounts lessons from their first ML project, emphasizing that data cleaning—handling missing values, fixing data types, and understanding the dataset—matters more than choosing the right model. The article walks through basic pandas commands like fillna, dropna, and astype. The author draws an analogy to Genesis 1 to illustrate that building incrementally and in order is essential.

• •Data cleaning is the foundation of ML, not a side task
• •Covers pandas basics: info, isna, fillna, drop, astype, to_datetime
• •Garbage in, garbage out — model quality depends on input quality

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