Machine Learning - Stanford - Coursera
1.0.0
1.0.0
  • Acknowledgements
  • Introduction
  • Linear Algebra Review
  • Types of Machine Learning
  • Supervised Learning
    • Linear Regression
      • Linear Regression in One Variable
        • Cost Function
        • Gradient Descent
      • Multivariate Linear Regression
        • Cost Function
        • Gradient Descent
        • Feature Scaling
        • Mean Normalization
        • Choosing the Learning Rate α
    • Polynomial Regression
      • Normal Equation
      • Gradient Descent vs. Normal Equation
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  1. Supervised Learning
  2. Linear Regression
  3. Multivariate Linear Regression

Feature Scaling

When there are multiple features, say size of the apartment, number of rooms, etc it may take a long time for the gradient descent to arrive at the global minimum of the cost function.

In such cases, it is recommended to scale all the features (say divide the size by 2000 and the number of rooms by 5), to get all features to the same scale.

Try to get all the features to have values approximately in the range [-1, 1].

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Last updated 5 years ago

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