What are some common data manipulation techniques in machine learning?
An example of an AI chatbot conversation about data manipulation techniques in machine learning.
What are some common data manipulation techniques in machine learning?
Common techniques include data cleaning, normalization, transformation, and feature engineering.
Can you explain feature engineering in more detail?
Feature engineering involves creating new input features from existing ones to improve model performance.
What tools can I use for data manipulation?
Popular tools include Pandas, NumPy, and Scikit-learn in Python.
How does data normalization affect model training?
Normalization helps in scaling the data, which can lead to faster convergence and better model performance.
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