Algorithm is a library of tools that is used to create intelligent applications.

computes most of information functions (joint entropy, conditional, mutual information, total correlation information distance) and deep information networks

Outlier detection for categorical data

Python package for calculating various information measures, including entropy, mutual information, transfer entropy, and more, with support for both discrete and continuous variables.

A Julia package that provides (feedback) particle filters for nonlinear stochastic filtering and data assimilation problems

Exercise solution to the Probability Theory course

This group project observed the impact of different student demographic variables such as parental education level, lunch option, ethnicity, gender and others on student's academic performance. The tools utilized were regression and conditional probability. R and Excel were used for these methodologies.

💬 Conditional Probability Clearly Explained

This repository is dedicated to providing a comprehensive learning path for mastering statistics in the field of data science

All the code, PDFs and LaTeX source from the UK Winning M3 Challenge 2022 team from Watford Boys Grammar School (15440).

Monty Hall Problem Game

3 machine learning projects

conditional probability density functional theory with examples

Create comprehensive customer profiles for each AeroFit treadmill product through descriptive analytics. Develop two-way contingency tables and analyze conditional and marginal probabilities to discern customer characteristics, facilitating improved product recommendations and informed business decisions.

Curso de adquisición y análisis de datos con técnicas multivariadas, teoría de gráficas, y redes.

Probability and Statistics - R Manual

A computational model simulating human-robot interaction.

A spam filter for SMS messages using the multinomial Naïve Bayes algorithm

calculating causal relationship between independent and dependent variables

This is a seminar paper that I wrote on the topic of conditional expectation as part of my measure-theoretic probability course.