/andrew-ng-old-matlab-machine-learning-course

🎓 Andrew Ng's machine learning course (matlab)

Primary LanguageMATLAB

andrew-ng-old-matlab-machine-learning-course

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Here are all the programming exercises from the Standford professor Andrew Ng's machine learning course.

Exercise 1

Linear regression

  • Calculate cost function for linear regression
  • Calculate gradient descent for linear regression

Exercise 2

Logistic regression & regularization

  • Sigmoid function for logistic regression
  • Cost for logistic regression
  • Gradient for logistic regression
  • Prediction function
  • Compute cost for regularized LR
  • Gradient for regularized LR

Exercise 3

Multiclass logistic regression

  • Regularized Logisic Regression
  • One-vs-all classifier training
  • One-vs-all classifier prediction
  • Neural Network Prediction Function

Exercise 4

Neural networks

  • Feedforward and Cost Function
  • Regularized Cost Function
  • Sigmoid Gradient
  • Neural Net Gradient Function (Backpropagation)
  • Regularized Gradient

Exercise 5

Regularized Linear Regression & Bias X variance

  • Regularized Linear Regression Cost Function
  • Regularized Linear Regression Gradient
  • Learning Curve
  • Polynomial Feature Mapping
  • Cross Validation Curve

Exercise 6

Support Vector Machines (SMV)

  • Gaussian Kernel
  • Parameters (C, σ) for Dataset 3
  • Email Preprocessing
  • Email Feature Extraction

Exercise 7

K-means Clustering & Principal Component Analysis (PCA)

  • Find Closest Centroids
  • Compute Centroid Means
  • PCA
  • Project Data
  • Recover Data

Exercise 8

Anomaly Detection & Recommender Systems

  • Estimate Gaussian Parameters
  • Select Threshold
  • Collaborative Filtering Cost
  • Collaborative Filtering Gradient
  • Regularized Cost
  • Gradient with regularization