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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.
The project utilizes Social Network Analysis (SNA) to comprehensively analyze global air travel dynamics and assess India's position in the aviation market.
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.)
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.
A complete Sales Analysis including Monthly basis analysis and Annual Analysis, Advanced Data Visualizations of Sales in different countries and also Analyzing the most Sold products in different countries.
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
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.