I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

This repository contains my final project for UT Austin's Data Analytics Bootcamp. My teammates and I explored a Wine Reviews dataset and built an interactive Tableau dashboard to recommend wines for a novice based on price, rating, variety, and country. We also built a machine learning model to train it to rate wine like an experienced sommelier.

Note : This Repository consists files of the ML Project - Robust Yield Prediction on Farm Units for a new food chain company , It's my Final academic project - PHD for the PG Program pursued in Data Science & Analytics @ Insofe.

In this project, I applied different regression models for rmse and mae on antenna dataset for predict signal strength.

A project to predict the average prices of Avocado in USA.

Finding High redshift quasars in large survey data using random forests. Code of Wenzl et al. 2021

RandomForest Regressor Model ML for predicting Price of House.

Development of an AutoML System to Predict the Compressive Strength of Concrete

Airline Fare Prediction using Regression

Построение различных моделей линейной регрессии для предсказания курса доллара

Supervised Machine Learning

Adjusting the prices of a product or service based on various factors in real time

🚘 Car-Choice 🚔 is a used car price prediction web app.

Car Price Prediction: Machine Learning (Data Science) Project using CarDekho.com dataset predicting prices of cars

Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties

Click below to visit the website live

Predict precipitation to mitigate flood damage in Bangladesh

Simple Application for predicting price of the flight. It uses sklearn pipeline to perform preprocessing , feature selection and feature engineering and model building .The pipeline object is saved in a pickle file and used in the flask application for prediction