An interactive Dash application providing in-depth analysis of global mental health trends, leveraging advanced data science and visualization techniques. Designed for insightful exploration of the prevalence and impact of mental disorders.

Home Market Harvester is a Python tool for scraping OLX, otodom rental data, enabling property market analysis with automated local CSV storage.

Stock Price Prediction Using LSTM is an AI-powered tool built with Python, TensorFlow, and Streamlit. It lets users train LSTM models on real-time stock data and visualize predictions interactively.

Published in GigaScience. Web app for post-GWAS/QTL analysis that performs a slew of novel bioinformatics analyses to cross-reference GWAS/QTL mapping results with a host of publicly available rice databases

This dashboard is a tool that shows the prevalence and patterns of mental health illness as well as the related health care service based on county-level data among the United States. It also compares the public interests in mental health with the data from Google Search Trends.

This project develops a Power BI dashboard to analyze home loan data, providing insights into loan applications, sanctions, disbursements, and recoveries. It helps financial institutions optimize loan processes and improve recovery strategies through data-driven decision-making.

An interactive Excel dashboard for analyzing bike sales data, featuring dynamic slicers, visual breakdowns by category, and key performance metrics. Designed to help users explore sales trends and performance over time. Inspired by Alex The Analyst’s Excel dashboard tutorial.

An interactive dashboard to explore analyze and visualize data with extremely, and a flask API

Interactive dashboard visualizing US flight delays and schedules, with dynamic filtering by city and year.

Sales Analysis - Sprocket Central Pty Ltd: This repository presents an in-depth analysis of sales data for Sprocket Central Pty Ltd. Discover key trends, best-selling products, optimal advertising timing, and actionable recommendations for growth. The interactive dashboard provides comprehensive visualizations, empowering stakeholders.

This project analyzes IPL (Indian Premier League) 🏏 data from 2008-2017 using Tableau 📊 to create interactive dashboards. It explores match outcomes, player performances 🏅, and team statistics 📈, offering insights into trends, top players 🌟, and team performances. The project uses `matches.csv` 📁 and `deliveries.csv` 📂 datasets to visualize

An interactive dashboard visualizing public sentiment and perceptions on American politics and the future of democracy, based on August 2018 survey data.

An interactive dashboard that visualises global happiness data (2020-2024), allowing users to explore key factors affecting happiness by continent and country.

A data analytics project for exploring housing prices in King County, WA. Compare city and countryside properties with an interactive app and gain detailed insights into real estate market trends.

The Supermarket Sales Dashboard offers a concise overview of sales performance, featuring key metrics and detailed analyses by product, category, and time period. Interactive filters enable data-driven decisions to improve profitability and efficiency.

This is the seventh project for the AI engineering master. The main goal is to develop a highly robust model, capable of automatically classifying flowers with the best possible F1-score (macro) on the test dataset. I need to use techniques such as data augmentations, transfer learning with PyTorch's timm library, YOLO for detections

Data visualization dashboard designed to provide insights into railroad incidents in the US.

Analyze healthcare data to identify key trends, risk factors, and actionable insights using Tableau dashboards and Python preprocessing. Enhance healthcare decision-making with interactive visualizations and data-driven approaches.

The Attrition Analytics Dashboard uses Power BI to analyze and visualize employee attrition trends, providing actionable insights to company for making strategic decisions.

A machine learning web application that predicts used car prices based on brand, age, and mileage using linear regression models. Built with Streamlit for an interactive, user-friendly interface and data visualization.