DAIVI is a reference solution with IAC modules to accelerate development of Data, Analytics, AI and Visualization applications on AWS using the next generation Amazon SageMaker Unified Studio. The goal of the DAIVI solution is to provide engineers with sample infrastructure-as-code modules and application modules to build their data platforms.
Terraform module to create and manage a SageMaker studio
It's just a terraform code for build a sagemaker notebook instance infrastructure to an AWS account. The code created a sagemaker notebook instance and needful things with a click. Maybe it's helpful to ML/DE Engineers.
Setting up an MLOps pipeline using AWS services
Global Aurora PostgreSQL Serverless V2 Database with Disaster Recovery and In-Database Machine Learning Capabilities
Build systems based on containisation and cloud infrastructure.
The project involves developing an AI-powered system to extract and analyze data from handwritten logbooks and service records using AWS native services. The goal is to create a scalable, secure, and efficient solution with a robust project structure, modern tech stack, and DevSecOps best practices.
Another Aws MlOps pipeline with Glue and Sagemaker, automated with Terraform and CICD
Tutorials and source code to train YOLOv11 on AWS SageMaker with Terraform for infrastructure setup
Discover a next-gen video search solution that uses AWS SageMaker, S3, OpenSearch, ECS Fargate, and Lambda. It extracts deep semantic features from videos for precise and scalable search beyond traditional keywords.
A Terraform module to deploy a Hugging Face PyTorch model on a serverless AWS endpoint.
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