A Python-based data analysis project exploring sugarcane production across countries. The project includes data cleaning, exploratory analysis, visualizations using Seaborn and Matplotlib, and correlation analysis to uncover patterns and insights in the dataset.

AI-enabled agricultural analytics and decision support platform for crop intelligence, state-wise production analysis, interactive visualizations, and data-driven policymaking.

Projeto de análise de dados envolvendo uso restrito do Scikit-Learn em uma base de dados de sementes.

Semantic segmentation model for counting wheat heads in field images, designed for yield estimation, flowering time detection, and field maturity assessment.

A curated collection of AI, ML, cybersecurity, and web projects by a VIT Bhopal CS student and hackathon enthusiast.

Interactive Crop Production Analysis Dashboard using Python, Pandas, Plotly and Streamlit.