Goal is to predict the concrete compressive strength using collected data

A Machine Learning exploration evaluating various models to predict Airbnb prices, culminating in an optimized Gradient Boosting Regressor.

Predicción del precio de venta de las viviendas en venta y de las viviendas en alquiler de Barcelona.

Predicting cement strength

Predicting genetic disorder and disorder subclass based on familial history and its effects

Analysis of flight systems to check the effectiveness of using Twitter data in conjunction with traditional datasets to improve predictions.

This project provides the best possible price of a used car by taking attributes such as Manufactured Year, Number of Cylinders, Condition, and many more as inputs. Out of all models tested, the Random Forest model predicted the prices closest to the prices listed on Craigslist. Developed a web app using the Flask API for the deployment of this …

The dataset provides information on crop production in India from 1997 to 2015. The Crop Production was predicted using Decision Tree Regressor, K Neighbours Regressor, Bagging Regressor, Random Forest Regressor and Gradient Boosting Regressor

Bagging is the term from "Bootstrap Aggregation Algorithm", That is for Low Bias & Low Variance

Predicting Compressive Strength of Concrete

machine learning regression

This mini-project involves experimenting with a variety of classification and regression models, exploring different techniques to understand their behaviors and applications in predictive analytics.

Aim of this project is to predict taxi fare based on available data. This dataset contains total 8 variables and 50000 indexes.