I am a certified DevOps engineer with a passion for building scalable and efficient systems. My expertise lies in Amazon Web Services (AWS), Docker, Kubernetes, Python, and Machine Learning. With a strong foundation in both software development and operations, I excel in creating automated pipelines, optimizing infrastructure, and deploying resilient applications.
- DevOps: Certified DevOps engineer experienced in implementing continuous integration, continuous deployment (CI/CD) pipelines, infrastructure as code (IaC), and automation.
- Amazon Web Service (AWS): Proficient in configuring, managing, and troubleshooting AWS environments for enterprise applications.
- Containerization: Skilled in Docker containerization to package, distribute, and run applications in isolated environments.
- Kubernetes: Experienced in deploying and managing containerized applications at scale using Kubernetes for orchestration.
- Python: Proficient in Python programming for scripting, automation, data analysis, and machine learning.
- Machine Learning: Knowledgeable in machine learning concepts, algorithms, and frameworks for predictive analytics and data-driven decision-making.
In this project, we will be taking a deeper look at Continuous Integration in practice. Here, will use several CI softwares like Jenkins, Ansible, SonarQube, etc to drive this implementation.
In this project, I improved the prediction accuracy of an existing machine learning model created by FAHAD MEHFOOZ. I was able to archive a 7.05% improvement in the model's accuracy by tuning few hyper parameters, introducing a validation dataset to guide against overfitting, etc.
Project Report | Project Repository
In this project, I explored the relationship (if any) between population growth of a country and it's energy consumption. It was surprising to find out that there is somewhat a negative relationship between Population Growth and Energy Consumption worldwide.
View Project Repository in Kaggle
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