Lecture 4 – Model parameter estimation - gradient#

Contents of this lecture

  • Basic meaning of the model regression

  • Define the regression (model optimization) problem

  • Estimation of the regression model (parameters)

    • Euler-Lagrange theorem (mathematically explicit solution)

    • Gradient descent algorithm (numerical approximation)

  • Numerical method: the gradient descent algorithms

  • Computer examples

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Please download the lecture through the following link Lecture 4: Model parameter estimation - gradient