A Python library for amortized Bayesian workflows using generative neural networks.

Probabilistic Programming and Nested sampling in JAX

A python script that automatise the training of a CNN, compress it through tensorflow (or ristretto) plugin, and compares the performance of the two networks

This is the repo for a python package that does model comparison between different regression models.

MADYS: isochronal parameter determination for young stellar and substellar objects

Brute Force Architecture Search

Searching for galaxy-assembly bias in the SDSS data

Quantization Aware Training

This project demonstrates the use of both Linear and Polynomial Regression models to predict salaries based on the position level of employees. By using a dataset that contains position levels and their corresponding salaries, this project showcases the differences between linear and polynomial models in fitting data and making predictions.

Automatic, efficient and flexible implementation of complex machine learning pipeline generation and cross-validation.

This project includes a python script that creates graphs by reading data from CSV files of models trained with YOLO.

The methods used in this thesis study consisted of Least Absolute Selection Operator (Lasso), Ridge, LightGBM, and XGBoost, Multiple linear regression, Ridge regression, LightGBM, XGBoost. With the use of a variety of regression methods it's being able to predict the sale price of the house. In addition, this model also helps identify which char…

This tool, developed in Python, interacts with various AI APIs, including ChatGPT, Copilot, Gemini, Llama, and Mistral language models. Users can submit requests and retrieve responses for the same input, with results organized in a CSV file for easy comparison. The tool computes similarities based on the expected outputs of different AIs.

Machine learning model comparisons for the Teleco Customer Churn data