Before You Train the Model: What My First ML Project Taught Me About Data Cleaning
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When I started my first data analytics and machine learning project, I wanted to get straight to the exciting part: training a model . I downloaded a dataset from Kaggle, chose a basic classification model, trained it, and started making predictions. But the results were strange . My predictions didn't look right, and metrics such as accuracy and ROC-AUC were much lower than I expected. My first thought was: Maybe I chose the wrong model. But the problem started before the model . I hadn't…
1Key Takeaways
- When I started my first data analytics and machine learning project, I wanted to get straight to the exciting part: training a model .
- I downloaded a dataset from Kaggle, chose a basic classification model, trained it, and started making predictions.
- My predictions didn't look right, and metrics such as accuracy and ROC-AUC were much lower than I expected.
- My first thought was: Maybe I chose the wrong model.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that when I started my first data analytics and machine learning project, I wanted to get straight to the exciting part: training a model .
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