GitHub - aysusayin/Machine-Learning-Algorithms: These are the essential machine learning algorithms that I implemented for Introduction to Machine Learning lecture in my university.

Implementation of Some ML Algorithms

Here you can find the implementations of the following machine learning algorithms:

Dimensionality Reduction
- PCA(Principle component analysis)
- LDA(Linear Discriminant Analysis)
Parametric and Non-Parametric Classification
- Parametric classification
- Mixture of Gaussians
- K-Nearest Neighbor
Multilayered-Perceptron

Also, there are codes for reviewing bias/variance dilemma, cross-validation and data visualization.

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
Classification.ipynb		Classification.ipynb
Dimensionality_Reduction.ipynb		Dimensionality_Reduction.ipynb
README.md		README.md
multilayer_perceptron.ipynb		multilayer_perceptron.ipynb
parametric_classification_bias_variance_dilemma_cross_validation.ipynb		parametric_classification_bias_variance_dilemma_cross_validation.ipynb
points2d.dat		points2d.dat