simple classification of hanzi by scikit-learn

A trained ML model for prediction of house prices in IOWA using Random Forest Regression technique

The project analyzed Asana user data to determine adoption rate and factors influencing adoption. After data cleaning, an adoption rate of 12% was calculated. Predictor variables were extracted and modeled using Random Forest and Decision Tree classifiers. Both models performed well, with Random Forest achieving 87% accuracy.

This repository shows the implementation of machine learning algorithms, data pipelines and data visualization with scikit-learn and python.

Flight Price Prediction Regression using Scikit-Learn

Explore machine learning models and optimization techniques.

Spotify Playlist Music Recommendation System

Employee Attrition Classification using Scikit-Learn

Analyzing the most affecting factors that deteriorate the health of a person and predicting the risk of developing dreadful diseases using Machine Learning.

Repositório de códigos de teste do Python feito por Rafael da Silva Braga

Criação de modelo de classificação capaz de identificar documentos como petições iniciais com base de treinamento em dados do CRETA

An AI model built to understand the sentiments transmitted through a phrase.

My Capstone for the HarvardX Course "Introduction to Data Science with Python"

Decision tree implementation using python scikit-learn

Winter24AICohort

A simple DNS atack detector based on DecisionTree built with scikit-learn

Use Python and Scikit-learn and Imbalanced-learn to predict credit risk. Compare the strengths and weaknesses of machine learning models. Assess how well a model works.