Welcome to the Machine Learning repository! 🚀 These files are based on my academic essays and each one (one per branch) describes another topic.
This repository is dedicated to exploring various Machine Learning techniques using Python. While it's not created entirely from scratch like some of our previous repositories, it leverages knowledge gained from our endeavors in Classification Techniques, Techniques of Multidimensional Statistical Analysis, Computational Intelligence, and Neural Networks. 🧠
- Building on Prior Knowledge: This repository complements our previous work and serves as a bridge to apply and expand upon the concepts explored in these repositories:
- Diverse ML Techniques: Different branches within this repository host various ML techniques. Explore these branches to gain insights into distinct ML methodologies and implementations. 🌐 Labs 3-6 are in polish for now, that's gonna be changed in the near future and also reports with conclusions and brother descriptions will be added.
- Lab1 - revision
- Lab2 - missing values
- Lab3 - decision trees and bagging
- Lab4 - random forst and boosting
- Lab5 - SVM algorithm
- Lab6 - oversampling and undersampling