What is Normalisation and Standardisation?
📰 Medium · Machine Learning
Learn when to use normalization and standardization in machine learning to improve model performance and why it matters
Action Steps
- Apply normalization to scale numeric data to a common range
- Use standardization to transform data to have zero mean and unit variance
- Compare the effects of normalization and standardization on model performance
- Configure data preprocessing pipelines to include normalization or standardization
- Test the impact of normalization and standardization on different machine learning algorithms
Who Needs to Know This
Data scientists and machine learning engineers benefit from understanding normalization and standardization to preprocess data effectively and improve model accuracy
Key Insight
💡 Normalization and standardization are essential data preprocessing techniques that can significantly impact machine learning model performance
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💡 Normalization vs Standardization: know when to use each to boost your ML model's performance
Key Takeaways
Learn when to use normalization and standardization in machine learning to improve model performance and why it matters
Full Article
When Should You Use Either, and Why It Matters. Continue reading on Data Science Collective »
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