climate-analytics

Enterprise climate intelligence platform spanning 275 years of temperature, CO₂, and sea level data. Interactive Plotly Dash analytics, geospatial choropleths, statistical early-warning detection, and a Tableau BI pipeline with export, workbook, and embedded Public dashboards.

Machine Learning based Monsoon Forecasting and Drought Risk Assessment system using Indian climate data, Random Forest classification, state-wise rainfall analytics, and interactive Streamlit visualization.

Application of the ETS model to forecast rainfall patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahwalnagar District, Punjab, Pakistan.

Application of the ARIMA model to forecast rainfall patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahawalnagar District, Punjab, Pakistan.

A complete data science pipeline for analyzing climate trends, detecting anomalies, and generating insights through interactive dashboards.

Hybrid cloud-edge weather ML platform that predicts near-term rainfall, auto-retrains models, and drives Raspberry Pi shutter actuation with CHIRPS historical rainfall enrichment.

Modern lakehouse for climate analytics with DuckDB + Parquet + Power BI + Prophet forecasting

An AI-powered weather analytics platform with predictive modeling, climate pattern visualization, and personalized microclimate monitoring

Calgary’s GHG and energy trends analyzed from 2000-2018 using cleaned datasets, a Power BI star schema, and DAX‑driven KPIs. Includes data engineering, modeling, and interactive dashboards to reveal emissions patterns, energy use insights, and policy‑relevant findings.

An end-to-end crop yield prediction pipeline using data preprocessing, exploratory data analysis, feature engineering, and machine learning to enable accurate, scalable, and data-driven agricultural forecasting.

geocoded weather data extractor

An end-to-end time series forecasting Streamlit web application predicting 12-month future Monthly Total & Maximum Daily Rainfall using Seasonal ARIMA (SARIMA). Benchmark evaluation against Seasonal Naive, Holt-Winters, and LSTM models.

Análise da temperatura máxima diária das capitais brasileiras utilizando Python, Pandas e visualização de dados com base em dados históricos do INMET.

An intelligent weather analytics and forecasting platform built with Python and Streamlit, featuring real-time meteorological data, interactive visualizations, predictive insights, and a modern responsive dashboard experience. I definitely didn't do it as a summer hobby project ¯\_(ツ)_/¯

Application of the ARIMA model to forecast PET patterns. Leveraging time-series analysis techniques, it predicts future rainfall levels by analyzing historical data specifically from Bahawalnagar District, Punjab, Pakistan.

Tableau: Climate-smart crop yield optimizer — NOAA, USDA NASS, SoilGrids & CME Futures

This project employs R programming to compute the Standardized Precipitation Evapotranspiration Index (SPEI), a widely used drought index. SPEI calculations were conducted for Bahawalnagar District, Punjab, Pakistan.

AI-powered Weather Intelligence Platform with real-time forecasting, alert analytics, FastAPI backend, automated visualizations, heatmaps, weather dashboards, and multi-city climate monitoring.