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Machine-Learning-Course-Assignments

Assignments of Machine Learning Graduate Course under supervision of Dr. Ehsan Nazerfard - Spring 2021

HW1 :

problem1:

  • implementation of linear Regression with gradient descent algorithm
  • fitting polynomial line with different degrees on signal data (univariate)

plots:

Fitting Plots:

image

Pace Size vs Iterations plot :

image

Error plot of train and test for degree 7:

image

Problem2:

  • getting familiar with concepts such as: correlation, multivariate linear Regression, feature selection, Regularization, Normal Equation, ...

plot of Data:

image

Correlation Diagram:

image

Error vs Iterations:

image

Pace Size vs Iterations:

image

HW2 :

problem1:

  • implementaion of KNN on MNIST dataset and reporting accuracy, confusion matrix and plotting pictures.

part of Results:

image

problem2:

  • implementation of Naive Bayes Algorithm on Wine dataset, reporting accuracy using 6-fold-cross-validation and plotting ROC curve.

ROC curve:

image

problem3:

  • implementaion of Logistic Regression (one-vs-all) on MNIST dataset and plotting results.

part of Results:

image

HW3 :

problem1:

  • SVM using python libraries (linear, polynomial, RBF and sigmoid kernels)
  • reporting accuracy and F1-measure

problem2:

  • implementation of Ensemble methods: RandomForest, AdaBoost, Gradient Boosting
  • reporting accuracy and confusion Matrix.

HW4 :

problem1:

  • implementation of KMeans clustering Algorithm

Results on first dataset:

image

Results on second dataset:

image

Results on third dataset:

image

problem2:

  • implementation of DBScan clustering Algorithm
  • reporting purity measure

Results on first dataset:

image

Results on second dataset:

image

Results on third dataset:

image

problem3:

  • implementation of Hierarchical clustering Algorithm

Results:

image

problem4:

  • implementation of Reinforcement Learning (Deep Q Network) in Mountain Car Environment.

Plots:

image

image

image