1. Feature Scaling
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make gradient descent run much faster
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converge in a lot fewer iterations
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no need in normal equation method, but while using gradient descent, it’s still important
2. Learning Rate α
- α is too small: slow convergence.
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α is too large: may not decrease on every iteration and thus may not converge.
3. Normal equation method
