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Welcome to the coursera-machine-leaning wiki!

• 1주차

  • ML:Introduction
  • ML:Linear Regression with One Variable
  • ML:Gradient-Descent
  • ML:Linear-Algebra-Review

• 2주차

  • ML:Linear Regression with Multiple Variables
  • ML:Octave-Tutorial

• 3주차

  • ML:Logistic Regression
    • Classification and Representation
    • Logistic Regression Model
    • Multiclass Classification
  • ML:Regularization
    • Solving the Problem of Overfitting

• 4주차

  • ML:Neural Networks: Representation
    • Motivations
    • Neural Networks
    • Applications

• 5주차

  • ML:Neural Networks: Learning
    • Cost Function and Backpropagation
    • Backpropagation in Practice

• 6주차

  • ML:Advice for Applying Machine Learning
    • Evaluating a Learning Algorithm
    • Bias vs. Variance
  • ML:Machine Learning System Design
    • Building a Spam Classifier
    • Handling Skewed Data
    • Using Large Data Sets