Welcome to my bilingual machine learning repository!
Here you'll find concise cheatsheets, theoretical summaries, and hands-on tutorials for the most important ML algorithms – available in both English and Polish 🇬🇧🇵🇱.

Witam w moim dwujęzycznym repozytorium uczenia maszynowego!
Znajdziesz tu zwięzłe ściągawki, podstawy teoretyczne i praktyczne tutoriale najważniejszych algorytmów ML – dostępne po angielsku i po polsku 🇬🇧🇵🇱.

Welcome to the Machine Learning Cheatsheet Repository – a structured collection of short, practical tutorials and summaries of popular ML algorithms.
Each algorithm comes with a separate folder containing:

• README.md – description, theory, use cases, pros & cons
• tutorial.ipynb – a Jupyter Notebook with hands-on code examples
• references.md – useful links, documentation, and papers

We provide materials in two languages:

• pl/ – Polish version
• eng/ – English version

• Linear Regression
• Logistic Regression
• Decision Tree
• Random Forest
• Gradient Boosting
• Support Vector Machine (SVM)
• k-Nearest Neighbors (KNN)
• Naive Bayes
• K-Means Clustering
• Hierarchical Clustering
• Principal Component Analysis (PCA)
• Multi-Layer Perceptron (MLP)
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• Transformer-based Models (BERT, GPT)
• Autoencoders
• DBSCAN
• Gaussian Mixture Models (GMM)

We welcome contributions!
You can:

• Add new tutorials or notebooks
• Improve descriptions or add references
• Translate content between PL/ENG
• Suggest new models or techniques

Please open a pull request or issue to join us!

This project is licensed under the MIT License.

Created with passion by [Tymoteusz Miller / University of Szczecin / AI Impact Hub].
Let’s make machine learning more accessible, one model at a time!