OrestisMk

Cardiotocography-classification-with-Svm-and-Mlp

This project compares the classification accuracy of SVM and Mlp on the cardiotocography dataset.

git-practice

git_practice

Knn-Rf-Classification-Breast-Cancer

Comparison of the performance of knn and random forest

missing-semester

The Missing Semester of Your CS Education 📚

OrestisMk-Multivariate-forecast-with-VAR-SVR-RNN-LSTM

Forecasting exchange rates by using commodities prices

practice-rebase-off-platform-project

codeacedemy example

RF-Q_learning-taxi_driver--Lunanlander-Policy-gradient-

This is a project of reinforcement learning which contains two different environments. The first environment is the taxi driver problem in 4x4 space with the simple Q-learning update rule. In this task, we compared the performance of the e-greedy policy and Boltzmann policy. As a second environment, we chose the LunarLander from the open gym. For the implementation of the project, the Policy gradient has been selected.

TestingFramework

End2End testing Framework with selenium

Time-series-data_manipulation

Manipulation of time series data and forecast CAD/USD currency using commodities

OrestisMk/OrestisMk-Multivariate-forecast-with-VAR-SVR-RNN-LSTM

Forecasting exchange rates by using commodities prices

OrestisMk/Knn-Rf-Classification-Breast-Cancer

Comparison of the performance of knn and random forest

OrestisMk/Cardiotocography-classification-with-Svm-and-Mlp

This project compares the classification accuracy of SVM and Mlp on the cardiotocography dataset.

OrestisMk/git-practice

OrestisMk/git_practice

OrestisMk/missing-semester

The Missing Semester of Your CS Education 📚

OrestisMk/practice-rebase-off-platform-project

codeacedemy example

OrestisMk/RF-Q_learning-taxi_driver--Lunanlander-Policy-gradient-

This is a project of reinforcement learning which contains two different environments. The first environment is the taxi driver problem in 4x4 space with the simple Q-learning update rule. In this task, we compared the performance of the e-greedy policy and Boltzmann policy. As a second environment, we chose the LunarLander from the open gym. For the implementation of the project, the Policy gradient has been selected.

OrestisMk/Time-series-data_manipulation

Manipulation of time series data and forecast CAD/USD currency using commodities