Repository: hassan11196/MachineLearningExercises
Description: Machine Learning by Stanford University. Taught by:  Andrew Ng
Primary language: MATLAB
Topics: ml, machine-learning, andrew-ng-machine-learning, andrew-ng, coursera-machine-learning, octave, matlab

# Machine Learning Exercises
## Coursera Course :  Machine Learning by Stanford University

- [Exercise 1 - Linear Regression](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex1)
  - [Linear Regression Cost Function](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex1/ex1/computeCost.m) 
  - [Gradient Descent](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex1/ex1/gradientDescent.m)
  - [Normal Equations](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex1/ex1/normalEqn.m)

- [Exercise 2 - Logistic Regression](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex2)
  - [Logistic Regression Cost Function](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex2/ex2/costFunction.m)
  - [Logistic Regression Regularized Cost Function](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex2/ex2/costFunctionReg.m)
  
- [Exercise 3 - Multi-class Classification and Neural Networks](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex3)
  - [Multi-class Classification](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex3/ex3/ex3.m)
  - [Vectorizing Logistic Regression](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex3/ex3/lrCostFunction.m)
  - [One-vs-all Classification](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex3/ex3/oneVsAll.m)
  - [Neural Network Prediction Function](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex3/ex3/ex3_nn.m)
  
- [Exercise 4 - Neural Networks Learning](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex4)
  - [NN Feedforward and Cost Function](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex4/ex4/nnCostFunction.m)
  - [Sigmoid Gradient](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex4/ex4/sigmoidGradient.m)
  - [Backpropagation](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex4/ex4/nnCostFunction.m)
  
- [Exercise 5 - Regularized Linear Regression and Bias vs Variance](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex5)
  - [Regularized Linear Regression](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex5/ex5/linearRegCostFunction.m)
  - [Polynomial Regression](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex5/ex5/polyFeatures.m)
  
- [Exercise 6 - Support Vector Machines](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex6)
  - [SVM with Gaussian Kernels](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex6/ex6/svmTrain.m)
  - [Spam Email Classification](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex6/ex6/processEmail.m)
  
- [Exercise 7 - K-means Clustering and Principal Component Analysis](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex7)
  - [K-means Clustering](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex7/ex7/computeCentroids.m)
  - [Dimensionality Reduction with PCA](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex7/ex7/pca.m)
  
- [Exercise 8 - Anomaly Detection and Recommender Systems](https://github.com/hassan11196/MachineLearningExercises/tree/master/machine-learning-ex8)
  - [Anomaly detection](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex8/ex8/selectThreshold.m)
  - [Collaborative filltering learning algorithm](https://github.com/hassan11196/MachineLearningExercises/blob/master/machine-learning-ex8/ex8/cofiCostFunc.m)



### Help Material : 
[what makes the gaussian kernel so magical for pca](https://stats.stackexchange.com/questions/131138/what-makes-the-gaussian-kernel-so-magical-for-pca-and-also-in-general)

[The Gaussian Kernel](https://mccormickml.com/2013/08/15/the-gaussian-kernel/)

Taught by:  Andrew Ng,