Computer Intelligence subject final project at UPC.

Open source gradient boosting library

Machine Learning model for price prediction using an ensemble of four different regression methods.

This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.

A Machine Learning Model built in scikit-learn using Support Vector Regressors, Ensemble modeling with Gradient Boost Regressor and Grid Search Cross Validation.

Example machine learning implementation to predict the residual bending moment capacity of corroded reinforced concrete beams tested under monotonic three or four-point bending. Data is collected from 54 experimental programs available in the literature.

Example machine learning applications for the determination of the residual yield force of corroded steel bars tested under monotonic tensile loading. Data is collected from 26 experimental programs avaialbe in the literature.

It was a competition on KAGGLE for prediction on the most sales products on bikes via their features

Soil moisture analysis , prediction and decision making to irrigate or drain water from field using Machine Learning ,numpy ,pandas , sklearn , matplotlib , Gradient Boosting Regressor model, linear regression model .

This repository enables an engineer to generate predictions for the mechanical bending performance of corroded beams, using a database of 725 corroded beams tested under monotonic bending. Outputs include the maximum bending moment, residual capacity percentage, yield load, yield displacement, and ultimate displacement.

Predict the employee burn out rate

A machine learning application aimed at predicting employee salaries based on various features such as experience, education level, location, etc. By using different models and techniques, the project seeks to present an optimized model for salary predictions.

A gradient-boosted tree framework to model the ice thickness of the World's glaciers

Simple GradientBoost

This repository contains machine learning model for predicting medical insurance cost using gradient boost algorithm.

Using Various Regression Algorithms to Predict House Sales

A BigMart Sales Prediction software designed to forecast sales using both supervised and unsupervised machine learning algorithms, leverages historical sales data, identifies data patterns.

Implemented a Decision Tree Regressor, a Gradient Boosting Regressor, and a Hierarchical Clustering Algorithm.

Predicting the score of a the home-team in an NBA game using Linear Regression

Machine Learning in Process Control