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What is the purpose of normalization in the context of neural networks?
Practice Questions
Q1
What is the purpose of normalization in the context of neural networks?
To increase the number of features
To ensure all input features have similar scales
To reduce the size of the dataset
To improve the model's interpretability
Questions & Step-by-Step Solutions
What is the purpose of normalization in the context of neural networks?
Steps
Concepts
Step 1: Understand that neural networks learn from data.
Step 2: Recognize that data can have different scales (e.g., one feature ranges from 0 to 1, while another ranges from 0 to 1000).
Step 3: Realize that if features have different scales, the model may focus more on the larger values and ignore smaller ones.
Step 4: Learn that normalization adjusts the scales of all features to be similar, often between 0 and 1 or -1 and 1.
Step 5: Know that by normalizing, each feature contributes equally to the learning process of the model.
No concepts available.
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