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daie
Data & Artificial Intelligence Engineering
by Godwin AMEGAH — Cloud & ML Engineer
Building production-grade ML systems and sharing knowledge on cloud-native data engineering, scalable AI architectures, and modern MLOps practices.
Topics I cover
Machine LearningCloud ArchitectureMLOpsDeep LearningData Engineering
Featured Projects
Recent work in ML and cloud engineering
activeEnd-to-End AWS Real-time Fraud Detection
Fraud detection system using machine learning models deployed on AWS for real-time transaction monitoring.
awsmachine-learningfraud-detection
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End-To-End Near Real-time Traffic Monitoring
Solution that leverages Apache Spark, Apache Airflow, and Docker to process and analyze traffic data.
bigdatastreamingreal-time
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Thoughts on ML, AI, and cloud engineering
LatestBuilding Scalable ML Systems in the Cloud
A comprehensive guide to designing and deploying machine learning systems that scale efficiently in cloud environments.
#cloud#machine-learning
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Self-training approach for short text clustering explained
PyTorch implementation of STC - Self-training approach for short text clustering.
#machine-learning#clustering
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MLOps Best Practices for Production Systems
Essential practices for deploying and maintaining machine learning models in production environments.
#mlops#machine-learning
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About the Author
Want to learn more about who's behind daie? Discover my background, experience, and approach to data and AI engineering.