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A full-stack sustainable gardening platform integrating AI-based plant disease recognition, climate-adaptive recommendations, and geospatial visualization. Built with Vue, AWS serverless architecture, and Python-based data and ML pipelines.
An interactive R Shiny dashboard analyzing Melbourne's metropolitan rail network. Features include supply-demand analysis, a custom Station Crowding Index (SCI), and network robustness simulations.
designed to visualize global trends in air pollution death through a series of dynamic charts, maps, and key metrics. By analyzing how well the current prototype communicates significant insights and supports user exploration, this study guides the next iteration of the design.
A responsive analytics dashboard with interactive charts, advanced filtering, cookie-based user preferences, and secure authentication. Share filtered views via URLs, backed by a robust API and data pipeline.
MoodRiser is a web application created during a 24-hour hackathon at the CodeForAll Fullstack Programming Bootcamp. Utilizing HTML, CSS, JavaScript, Python with Flask, and various APIs including Spotify and Google Books, and OpenAI, this SPA helps users manage their emotions through personalized content recommendations based on their current mood.
Objective, create an intuitive and user-friendly web-based application for visualizing and exploring NHANES data. This dashboard will enable users, including those with limited or no Python programming experience, to interact with NHANES data and generate informative visualizations to gain insights into various health-related aspects.
A Jupyter Notebook demonstrating the extraction and visualization of stock data for Tesla and GameStop, crafted for the Python Project for Data Science IBM Certification.
This is an Excel Project wherein we have applied formulas such as summits, maxims, minis, averageifs, countifs on a large data set. Have also created an interactive dashboard using pivot tables and various data visualisation tools. Presented data validation and conditional formatting. Have also presented VLookup, HLookup, IF and IFERROR Functions.
Performed exploratory data analysis (EDA) in python on the world happiness report datasets (for years 2015, 2016, 2017, 2018, and 2019) from Kaggle; to analyze how measurements of well-being can effectively help assess the progress of nations across the world.