Insights, tutorials, and experiences in AI/ML, backend development, and cloud architecture. Sharing knowledge and lessons learned from building enterprise-scale solutions.
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A comprehensive guide to implementing Retrieval-Augmented Generation (RAG) systems at enterprise scale using AWS SageMaker, including best practices for model deployment and monitoring.
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Learn how to implement robust MLOps pipelines using Kubeflow and MLflow, ensuring smooth transitions from model development to production deployment.
A detailed account of migrating from AWS WAF Classic to WAFv2 across hundreds of applications, including challenges faced and solutions implemented.
Explore advanced techniques for optimizing deep learning models including quantization, pruning, and knowledge distillation for production deployment.
A practical guide to designing and implementing microservices architecture using Spring Boot, with AWS cloud services for scalability and reliability.
Implementing robust A/B testing frameworks for machine learning models, including statistical significance testing and business impact measurement.
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