Aspiring ML Engineer | AWS AI ML Scholar'23 | Experienced in Deploying AI Systems | Python • Deep Learning • Cloud ML

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AAYUSH AGARWAL  • Peerlist

<a target="_blank" rel="noopener noreferrer" class="break-all link-break text-gray-500 hover:underline" href="http://TAZ.ai">TAZ.ai</a> is an innovative travel planning platform that leverages artificial intelligence to provide end-to-end trip planning solutions. From initial planning to booking transportation, accommodations, and activities, TAZ.ai creates personalized travel experiences with hassle-free itineraries.<h3>🔮 Future Roadmap</h3><h3>1️⃣ Device Integration</h3><ul><li>Smartwatch apps for real-time travel updates.</li><li>VR integration for immersive destination previews.</li><li>Voice assistant compatibility.</li></ul><h3>2️⃣ Enhanced Features</h3><ul><li>Real-time booking integration.</li><li>Multi-language support.</li><li>Personalized travel recommendations.</li><li>Group travel coordination.</li></ul>

TAZ.AI

Discover Your Perfect Style with AI-Powered FashionStyle AI is a fashion product search engine powered by AI that enables both text-to-image and image-to-image search capabilities using CLIP for multimodal embeddings, Qdrant for vector storage and queries, and AWS S3 for image hosting; developed FastAPI backend, Dockerized it, and deployed on AWS ECS.Integrated with AWS S3-hosted frontend via AWS CloudFront, secured API with AWS API Gateway for HTTPS, enabling efficient product recommendations.Key Features:<ul><li>Semantic search system for fashion product images using CLIP model for generating image embeddings, Qdrant as the vector database for efficient similarity searches, and AWS S3 for storing image data.</li><li>Served the backend API with FastAPI containerized it using Docker, and deployed it on AWS ECS for scalable hosting and integrated the backend with a frontend hosted on AWS S3 and distributed via AWS CloudFront.</li><li>Utilized AWS API Gateway to serve the API over HTTPS, enabling secure and efficient end-to-end user queries for image-based product recommendations.</li></ul>