A data-driven analysis of movie success factors, including genre popularity, production company performance, language trends, and financial success. This project explores influences on a movie’s ratings, popularity, and revenue through feature engineering, data preprocessing, and visualizations.
Our project aims to bring together teachers and students and provide a platform for better connectivity.
Python-based ETL pipeline that automates data transfer from Google Sheets to PostgreSQL.
Analysis of Swiggy's food delivery data across Indian cities, examining restaurant metrics, cuisines, and customer preferences.
The project utilizes Social Network Analysis (SNA) to comprehensively analyze global air travel dynamics and assess India's position in the aviation market.
Python implementation of K-Means clustering data science algorithm
🙋Completed all the assignments based on SQL, EXCEL, PYTHON, EDA, MACHINE_LEARNING, LINEAR REGRESSION,
This project aims to compare the performance of Facebook and AdWords advertising campaigns through A/B testing. By analyzing key metrics such as ad views, clicks, conversions, and costs, we seek to identify the most effective platform for optimizing advertising strategies.
A machine learning model to predict whether clients of a Portuguese banking institution will subscribe to a term deposit, based on data from direct marketing campaigns involving phone calls.
This project aims to develop a deep learning-based system for classifying diatom images, which can be used for water quality monitoring. Dataset sourced from KAGGLE (URL provided below.)
Uses machine learning to analyze e-commerce data, uncover insights, and offer actionable suggestions
The Power BI project on the terrorism dataset offers an interactive and visually engaging data analysis solution. It utilizes charts, graphs, and maps to explore global terrorism incidents, providing insights into patterns, trends, and hotspots.
An in-depth analysis of a movie rental store using SQL & Python to uncover trends in customer behavior, rental patterns, and revenue insights. Features data cleaning, EDA, SQL queries, and visualizations for data-driven decision-making. 🚀
This project has all the solutions for weekly Tableau prep challenges from https://preppindata.blogspot.com/.
Analysis of sale price per square foot, gross rent, and available housing units for various neighborhoods in San Francisco.
Predicting discounted prices of the listed products from Amazon & Flipkart based on their ratings, reviews and actual prices using models like Random Forest Regressor, KNN Regressor, etc.
Operation & Metric Analysis
Implementation of a noise level analysis system for a country. Utilizes both sensor data and computer simulations to analyze noise levels, followed by calculation of key metrics
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