logistic regression

This project focuses on developing a binary classification model to accurately predict whether a mushroom is edible or poisonous based on a given dataset. The dataset, a cleaned version of the original Mushroom Dataset from UCI, includes features such as cap diameter, cap shape, gill attachment, gill color, and others. The goal is to create a reliable model that can assist in identifying potentially harmful mushrooms.

Evaluación de distintos modelos para clasificar aguas entre potables y no potables

Exercícios de programação da disciplina MAC0460 - Introdução ao Aprendizado de Máquina ministrada pela professora Nina Sumiko Tomita Hirata no Instituto de Matemática e Estatística da Universidade de São Paulo no primeiro semestre de 2021.

Machine Learning - Binary Classification

Machine Learning - Binary Classification

Machine Learning - Binary Classification (NLP)

Machine Learning - Binary Classification (NLP)

Machine Learning - Multiclass Classification

Machine Learning - Binary Classification

Machine Learning - Multiclass Classification

Machine Learning - Multiclass Classification

Machine Learning - Binary Classification