This repository contains a collection of lab notebooks focused on supervised machine learning techniques. Each notebook explores a specific algorithm or workflow through structured experimentation and analysis.
NN_Lab.ipynb: Implementation and experimentation with a basic neural network.SVM_Lab.ipynb: Support Vector Machines (SVM) for classification, including kernel variations.Trees_AdaBoost_Lab.ipynb: Comparison between decision trees and boosting methods using AdaBoost.KPCA_SVR_Lab.ipynb: Dimensionality reduction via Kernel PCA followed by regression with SVR (Support Vector Regression).
- Experiment with classical and advanced supervised learning models.
- Study the impact of transformations such as kernel mapping and dimensionality reduction.
- Evaluate model performance and limitations using synthetic and real datasets.
Clone the repository and install the dependencies:
git clone https://github.com/archer-paul/ml-methods-labs.git
cd ml-methods-labs
pip install -r requirements.txt