command-line Tris game (project for university exam)

ML

Algoritmos para visión artificial implementados en C++

Machine learning projects

Inteligencia Artificial - Facultad de Informática de A Coruña

This project provides the solution to the puzzle game named Word Collapse using Artificial Intelligence algorithms.

Tic Tac Toe game vs AI Computer using Alpha Beta Pruning. AI is designed to select path of min # of moves to defeat human player. Coded in Python

Examples inspired from Bio-Inspired Artificial Intelligence, Floreano and Mattiussi.

My second data science project where I experiment with the famous Titanic dataset

Classification algorithms to identify images by their bitmaps

Dry Natural Gas Production Prediction of the United States

🤖 Artificial intelligence (neural network) proof of concept to solve the classic XOR problem. It uses known concepts to solve problems in neural networks, such as Gradient Descent, Feed Forward and Back Propagation.

Solving missionary cannibal problem using different search strategies in C

This repository contains algorithms of Artifical Intelligence that I implemented based on Prof Rafael Rossi videos availables on his Youtube channel (https://www.youtube.com/c/RafaelRossiTech) during my journey studing Artificial Intelligence

This has been a machine learning quest to classify cancer types using gene expression data, utilizing powerful tools and techniques to preprocess, train and evaluate models. The ultimate goal, to save lives through early diagnosis with high accuracy and precision.

The aim of our project is to make a system that will help in connecting the people who find some missing people or object and the people who got their person or object missing.

In this case, we train our model with several medical informations such as the blood glucose level, insulin level of patients along with whether the person has diabetes or not so this act as labels whether that person is diabetic or non-diabetic so this will be label for this case.

Make your daily life things easy.

Techniques for designing algorithms using divide and conquer, greedy methods, dynamic programming, and backtracking by emphasizing on analysis of efficiency, design techniques for NP problem domain.