Flight Ticket Price Prediction

Accurate flight ticket price prediction project using XGBoost regression, benefiting both airlines and passengers. Employing a supervised learning approach with labeled historical data to enhance pricing trend insights.

Product-Review-Analysis---FlipKart-Amazon

Utilizing ML and NLP, this project analyzes customer reviews on e-commerce platforms, categorizes sentiments, computes ratings, and generates ranking tables for mobile phones. It aims to enhance FMCG product quality and customer satisfaction.

Industrial Copper Modeling

The Industrial Copper Modeling project aims to address challenges in the copper industry related to sales prediction and lead classification. It involves the development of machine learning models for predicting selling prices and classifying leads as either successful (WON) or unsuccessful (LOST).

E-Commerce-Analytics-Project

This project focuses on analyzing an e-commerce dataset to derive valuable insights that can aid in making informed business decisions. The dataset encompasses various aspects of e-commerce transactions, including customer behavior, product details, and sales information.

Airbnb-Analysis

The Airbnb Analysis Project seeks to optimize property listings and enhance user experiences by analyzing data on trends, preferences, and pricing dynamics. With a focus on data science, the project aims to provide valuable insights for hosts and improve booking satisfaction for guests.

PhonePe Pulse

PhonePe Pulse is a data visualization project that showcases digital payment trends in India using an interactive map and insightful charts. The project gathers data from PhonePe's extensive transaction history and presents it in an easily digestible format.

Movies_Metadata_Cleaning

Cleaned and standardized the Movies Metadata dataset to address issues such as missing data and mismatched data types, ensuring data quality and consistency.