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The tasks accompanying the "Stochastic Methods in Machine Learning" classes at AGH University of Science and Technology in Krakow.

R implementation of Hierarchic Memetic Strategy (HMS).

The task accompanying the Optimization workshop at AGH AI Days.

The tasks accompanying the Evolutionary Algorithms classes at AGH University of Science and Technology in Krakow.

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Large Language Model Evolutionary Algorithm

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Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems

Streamlit demo app

Probability Distributions Explorer

Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

Testing cognitive reflection of Large Language Models

Hyperparameter tuning and evaluation for pyhms.

This repository contains a Python implementation of the Generalized Numerical Benchmark Generator (GNBG). The code is designed to work with a set of 24 pre-configured problem instances. The code operates independently of the GNBG generator file and only uses the saved configurations.

A high-performance topological machine learning toolbox in Python

High performance implementation of Vietoris-Rips persistence.

Python bindings and API for the flagser C++ library (https://github.com/luetge/flagser).

HMS evaluation and analysis. The comprehensive evaluation and analysis of the Hierarchical Memetic Strategy (HMS) optimization algorithm.

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