Land Use and Land Cover Classification Model
Developed a deep learning model for classifying Multi-Spectral Surface Reflectance Data from the LandSAT satellite for the purpose of developing Land Cover Maps for Fido State, Nigeria.
Iwinosa Osagie-Okah is a versatile full-stack and mobile developer with proven experience building scalable, high-performance applications across web and mobile platforms. He is highly skilled in React Native, Next.js, and TypeScript, and has a strong backend foundation with Express.js, FastAPI, Django, and NestJS. His expertise extends to database management with PostgreSQL, CI/CD pipelines with Docker and GitHub Actions, and styling with Tailwind CSS and PandaCSS. Iwinosa has delivered production-grade projects involving…
Developed a deep learning model for classifying Multi-Spectral Surface Reflectance Data from the LandSAT satellite for the purpose of developing Land Cover Maps for Fido State, Nigeria.
Built a microservice that communicated with Chowdeck and Google Maps to provide real-time delivery pricing information and delivery management functionality for a Shopity store

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Iwinosa Osagie-Okah is a versatile full-stack and mobile developer with proven experience building scalable, high-performance applications across web and mobile platforms. He is highly skilled in React Native, Next.js, and TypeScript, and has a strong backend foundation with Express.js, FastAPI, Django, and NestJS. His expertise extends to database management with PostgreSQL, CI/CD pipelines with Docker and GitHub Actions, and styling with Tailwind CSS and PandaCSS. Iwinosa has delivered production-grade projects involving…
Developed a deep learning model for classifying Multi-Spectral Surface Reflectance Data from the LandSAT satellite for the purpose of developing Land Cover Maps for Fido State, Nigeria.
Built a microservice that communicated with Chowdeck and Google Maps to provide real-time delivery pricing information and delivery management functionality for a Shopity store
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