Running Monte Carlo - Markov Chain algorithm on synthesized spectral models made by CLOUDY to compare them with data from CECILIA survey

This repository provides a systematic implementation and evaluation of advanced statistical measures for data repeatability, grounded in the methodologies outlined in "Statistical Analysis of Data Repeatability Measures" by Wang et al. (2020). It focuses on applying and extending metrics such as discriminability, fingerprinting, and rank sums

Call-center discrete event simulation project mostly done using numpy and simple data structures.

A Turkish language model using syllable and character based n-grams (1-gram, 2-gram, 3-gram) built on the Turkish Wikipedia Dump dataset for random sentence generation for NLP tasks and language modeling.

Escrevendo um plugin experimental para interpolação (IDW e Krigagem) no QGIS.

A neural network calculates your chance of finding love.

"This repository serves as a comprehensive resource for understanding and applying Regression techniques in achine learning and statistical modeling."

Statistical models

A plugin that runs the boids model in QGIS

Analyse efficacy of your own confidence interval (CI) methods

A Markov Model DNA sequence generator to generate pseudo-replicate sequences based on an input sequence

The ideal way to evaluate binary classification models.

In this repository are contained all the codes for the data analysis of batch accumulation test for PHA production.

Generator of new data with the same probability distribution and statistics from a frecuency table or a dataset or or alternatively bothboth.

Python-first access to R’s brms with proper parameter names, ArviZ support, and cmdstanr performance. The easiest way to run brms models from Python.

Theoretical notes on Machine Learning

Artificial Collective consciousness: A New Way To Study, Learn and Have A Fun!

Plotly Dash app that animates Bayesian updates of beta distributions with binomial data

The purpose of this analysis is to obtain a forecasting model by the relationship between different automobile component combination and their price and predict prices of possible automobile component combination.

Project designed to automatically pick parameters (AutoML) for multiple models for rapid feature engineering.