There are 2 repositories under random-forest-regression topic.
Predicting flight ticket prices using a random forest regression model based on scraped data from Kayak. A Kayak scraper is also provided.
This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates
Machine Learning Model for Order Demand Prediction based on historical Order data - Built for Swiggy Hackathon 2018
A Machine Learning Project that uses Random Forest Regressor model to predict used cars price based on some attributes such as kilometers driven, age, number of previous owners etc.
A data-driven tool to predict the reaction order of homogeneous gas-phase reactions. Includes machine learning experiments on the NIST Chemical Kinetics Database.
Using Time Series forecasting and analysis to predict Walmart Sales across 45 stores.
In this project we are comparing various regression models to find which model works better for predicting the AQI (Air Quality Index).
Automated ML pipeline with Python, Docker, Luigi, SciKit-Learn and Pandas to predict wine quality ratings
Algerian Forest Fire Prediction
Insurance cost predictor
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
The project would generate report of the result of the students and is also capable of concluding the result analysis report of the students as in tables, figures in Excel Sheet. The project is based on python which will use the web scraping technique used to launch the website from an automated software (as a web browser) to visit the website (RGPV) and fetch data as results of an individual student, Data analysis which is used to inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decision-making, in this case with help of machine learning the prediction for the score of the students can be generate and shown in the format of figure as graph which concludes average score of batch, current batch, prediction of the score for the remaining semesters.
This repository contains Python functions for predicting time series.
Rate your music out of 5 stars (interactive)!
Predicting how much loan will be approved
A Flask based Web Application that Predicts the Flight Price using RandomForestRegressor.Its GUI is based on Swagger API. This is hosted on the Heroku platform.
A machine learning project that predicts the price of used cars in the UK
The project aims to develop models that can forecast traffic congestion, aiding in effective traffic management and planning.
A thorough analysis of opensource Fitbit data is performed. The key findings are highlighted and discussed. The analysis provided herein is performed using 940 data points collected from 33 distinct users. Machine Learning Models are used to solve a regression problem using Multiple Linear Regression, Random Forest and Extreme Gradient Booster
This is a data analysis project with price prediction with Random Forest Algorithm of cars in Indian market and also consist of customer segmentation with the help of Clustering analysis with KNN algorithm
Aim of the project is to predict the fare of the flight.
Environmental Studies (P/F course) - End Semester Project
Drift Detection in Gas Sensor Array at Different Concentration Levels β’οΈ
A simple implementation of Random Forest Regression in python.
Predicting the sales of a store
Natural Gas Price Prediction System Using IBM Watson services
K-Means Clustering for the coping strategies of Brief COPE Questionnaire
Machine Learning Prediction Software Based on Classification and Regression Based on Processor [CPU] Specifications
AI Nexus π is a streamlined suite of AI-powered apps built with Streamlit. It features π StyleScan for fashion classification, π©Ί GlycoTrack for diabetes prediction, π’ DigitSense for digit recognition, πΈ IrisWise for iris species identification, π― ObjexVision for object recognition, and π GradeCast for GPA prediction with detailed insights.
This project aims to estimate building's height on historical maps based on the building's characteristics in the present time. Random forest regression are used to estimate the building's height, and the result will be visualized into 3D City Model Visualization that could be used for further spatial analysis.
A model was built to predict the total insurance claim amount payable by the insurance company using machine learning techniques such as regression in python.
This is a predictive analysis of a dataset from CAR DEKHO. It predicts Car Selling Price. This is an end to end machine learning model.