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Cloud & Infrastructure
Hands-on AWS practice with compute, storage, networking, IAM, monitoring and load balancing.
Building in Cloud, Data & AI
MG Ishaque.
I build practical cloud infrastructure, data workflows and machine-learning projects — with a focus on learning by building.
$ whoami
name: "MG Ishaque"
focus: ["Cloud", "Data", "AI"]
stack: ["AWS", "Python", "SQL"]
status: "building"
# always learning, always shipping
name: "MG Ishaque"
focus: ["Cloud", "Data", "AI"]
stack: ["AWS", "Python", "SQL"]
status: "building"
# always learning, always shipping
About
I'm developing across cloud engineering, data engineering and AI. My current work includes AWS hands-on labs, Linux/Git workflows, Python data science and machine-learning projects.
This portfolio is a living record of what I build, learn and document — not just a list of technologies.
Cloud
AWS • EC2 • EBS • ELB • IAM • CloudWatch
Data
Python • SQL • Pandas • NumPy
AI/ML
Scikit-learn • Deep Learning • LLMs
Workflow
Linux • Git • GitHub • Automation
Skills
A growing technical stack focused on building deployable, measurable projects.
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Data & Python
Data analysis, preprocessing, SQL and reproducible Python workflows for analytics and ML.
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AI & Machine Learning
Classical ML and a growing focus on deep learning, LLMs, RAG and MLOps.
Projects
Selected work and hands-on labs. More projects will be added as they are completed.
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AWS Cloud Labs
Documented AWS assignments covering IAM, CloudWatch, EBS, FSx and Elastic Load Balancing.
View on GitHub ↗🚀
ML Projects
Machine-learning projects exploring prediction, evaluation and practical model-building workflows.
Explore repositories ↗🧠
AI Engineering
Learning and experimentation around LLM applications, RAG, MLOps and agentic workflows.
Follow the work ↗Let's build something useful.
Interested in the work? Explore the code, projects and experiments on GitHub.
Visit GitHub ↗