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End-to-End-ML-Pipeline-on-AWS-SageMaker
End-to-End-ML-Pipeline-on-AWS-SageMaker PublicEnd-to-end ML training and deployment pipeline using AWS SageMaker.
Jupyter Notebook
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Network-Security-Analysis-System
Network-Security-Analysis-System PublicEnd-to-end ML pipeline for phishing URL detection. Deployed on AWS via Docker + ECR + EC2.
Python
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Transformer-Based-NLP-Pipeline-Hugging-Face-
Transformer-Based-NLP-Pipeline-Hugging-Face- PublicNLP pipeline using Hugging Face transformers, fine-tuned for text tasks. Containerized with Docker
Jupyter Notebook
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-ML-Lifecycle-Management-System-MLflow-DagsHub-BentoML-
-ML-Lifecycle-Management-System-MLflow-DagsHub-BentoML- PublicEnd-to-end MLOps workflow with MLflow tracking, DagsHub versioning, and BentoML serving.End-to-end MLOps workflow with MLflow tracking, DagsHub versioning, and BentoML serving.
Python
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-Multi-Cloud-ML-Deployment-System-AWS-Azure-
-Multi-Cloud-ML-Deployment-System-AWS-Azure- PublicML model deployment on both AWS and Azure for cloud-comparison and resilience.
Jupyter Notebook
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