My Projects

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Amazon Sales Trend Analysis

Analyzed Amazon reviews using Python and NLP to extract insights on customer sentiment, rating trends, and review themes. Built interactive dashboards with Plotly and maintained version control via GitLab. Focused on three products, showcasing data cleaning, EDA, and VADER sentiment analysis. .

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Trend Analysis

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Analysing & Predicting Sales Trends

Built ML models (Logistic Regression, Random Forest) to Analysing & Predicting products sales trends.

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Analysing & Predicting products sales trends

Student Dropout Predictor

Interactive web app predicting student dropout risk with visualizations.

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Project Walkthrough

MediCareDB: Scalable NoSQL-Based Healthcare Management System

MediCareDB is a document-oriented healthcare database system built using MongoDB and Python (PyMongo). The system features automated data generation, denormalization for performance, indexed queries, and aggregation pipelines. Optimized using indexing strategies and real-time performance tracking (executionTimeMillis), MediCareDB demonstrates how NoSQL databases outperform traditional SQL systems in scalability and flexibility for dynamic, high-volume medical data.

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Scalable NoSQL-Based Healthcare Management System

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Exploratory Analysis of Iris, Nile & MPG

EDA in Python and R to visualize dataset distributions and trends.

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House Price Prediction with Ridge Regression

Forecasted real-estate prices using Ridge Regression on a large dataset.

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COVID-19 Data Analysis

Global COVID-19 trend visualizations using Pandas and Matplotlib.

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Car Price Prediction by Random Forest

Random Forest Regressor to predict car prices with full evaluation.

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Car Prediction

HealthCareDB (SQL)

A SQL database design for managing hospital operations.

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