Predicting the bike count required at each hour for the stable supply of rental bikes.

Perform extensive Exploratory Data Analysis(EDA) on the Zomato Dataset. Building an appropriate Machine Learning Model that will help various Zomato Restaurants to predict their respective Ratings based on certain features deploy the Machine learning model via Flask

Kaggle competition : prediction of the energy uses with machine learning

Explore machine learning for automotive testing optimization. Predictive analytics to reduce testing time and environmental impact.

Video transition time estimation with different regression techniques

2020 DACON CUP - 최종 2위

Naive, XGBoost, AdaBoost and other Regressors

Temperature prediction for Machine Learning course.

This repository contains implementations of regression models on the Starbucks stock market. The goal is to provide a comprehensive understanding of the performance of these models. Also, implement metrics without relying on external machine learning libraries. ☕️📈

Development of a site where flight prices could be predicted.

Development of a ratings predictor for Zomato food places.

Predicted the energy consumed by various appliances using moisture content, temperature & other external conditions given in the data set. We used feature engineering techniques and the LSTM Network for training and got the best results. We were ranked 2nd out of 50+ participants after the final evaluation

This project utilizes housing features to develop a regression model for predicting housing prices.

Estimation of permeability reduction due to asphaltene deposition and precipitation with the help of machine learning algorithms

The main goal of this machine learning project is to build a machine learning model to predict the car price.

In this project we will predict the time taken by NYC taxis to complete their trips using regression.

Explore and predict the used car price by building the machine learning model based on the existing data. Then examining the model between the actual price and the predicted price.

This is a end to end data science project where the flight fare has been predicted using Random Forest model.

Loan Prediction Problem Analysis