What is the impact of data preprocessing on machine learning models?
An example of an AI chatbot conversation about the importance of data preprocessing in ML.
What is the impact of data preprocessing on machine learning models?
Data preprocessing is crucial as it improves the quality of data, leading to better model performance.
Can you give examples of preprocessing techniques?
Sure! Common techniques include normalization, handling missing values, and feature encoding.
How does normalization affect model accuracy?
Normalization helps in scaling the data, which can significantly enhance the convergence speed and accuracy of models.
What happens if I skip data preprocessing?
Skipping preprocessing can lead to poor model performance, overfitting, or even failure to train.
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