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

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

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

Reducing the cost & increasing efficiency of Merchant Ships

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

Diabetes mellitus, commonly known as diabetes is a metabolic disease that causes high blood sugar. The hormone insulin moves sugar from the blood into your cells to be stored or used for energy. With diabetes, your body either doesn’t make enough insulin or can’t effectively use its insulin.

My Python learning experience 📚🖥📳📴💻🖱✏

Developed a price prediction model using Random Forest Regression algorithm. Different graphs were created as a part of Exploratory Data Analysis. Feature Engineering was performed to make the data ready for building the model.Built an interactive dashboard using dash and plotly libraries

RandomForest Regressor Model ML for predicting Price of House.

A model for predicting the selling price of a used car using machine learning algorithms. This model is deployed in the Heroku Cloud Platform.

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

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.

Prepr's Machine Learning Challenge

Regression Machine Learning Project

Este trabajo se enfoca en la implementación de Limpieza, Análisis Exploratorio de Datos y Visualización de Datos para obtener conclusiones acerca del COVID-19 en Alemania.

Airline Fare Prediction using Regression

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.

Prediction of car prices using data from sahibinden.com

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.

In this project, we will predict the price for AMES House and learn Machine Learning Algorithms, different data preprocessing techniques such as Exploratory Data Analysis, Feature Engineering, Feature Selection, Feature Scaling and finally to build a machine learning model.