This is a production grade project which is used to classify eight different types of Skin Diseases using CNN. It is trained on top of VGG16 architecture and used MLFLOW for model versioning. It also uses DVC pipeline to automate the complete each stage of the project. Finally I have dockerized the project and Hosted In AWS using EC2 instance, ECR.
K3ai is a lightweight tool to setup quickly an AI stack: K8s + AI platforms and experiment your AI CI/CD workflows
AI-powered React Native Web project generator with conversational chat interface. Generate complete mobile-web compatible applications using Claude AI and GPT-4, modify them through natural language chat, and export ready-to-use code. Zero external dependencies, pure react-native-web implementation.
AI-powered mental wellness journal and personal coach that helps users track emotions, predict mood trends, and build healthier daily habits through smart, personalized support.
A production-ready system for crop disease diagnosis using classification Total Parameters: ~35M (Vision: 2.5M + Optional Language: 22M) Training Time: 7-10 days on CPU Inference Speed: <300ms on mobile phone
A tool for automating invoice processing, featuring both typed and handwritten invoice recognition. Built with Flask for the backend and React for the frontend, this tool streamlines data extraction and supports CSV export for efficient record-keeping.
PawMark is a platform for developers to build, schedule and monitor data pipelines.
RapidFire AI: Rapid Experimentation Engine for Customizing LLMs
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