About Me
I am an undergraduate student at Pancasila University with a strong interest in Artificial Intelligence and Machine Learning. I enjoy working with data and understanding how it can be transformed into meaningful insights through end-to-end ML systems. My curiosity in AI/ML has driven me to explore the full machine learning pipeline, from data preparation and model development to deployment and monitoring in real-world environments.
I have hands-on experience building ML pipelines using Python and implementing monitoring systems with Prometheus and Grafana to ensure reliability and performance. Alongside this, I am actively learning DevOps practices, including CI/CD workflows with GitHub Actions and Jenkins, containerization with Docker, and automation for scalable system deployment. My goal is to bridge machine learning and DevOps to build production-ready, reliable AI systems.
My Journey
Experience
Machine Learning Cohort 2024 H2
Bangkit Academy
Remote
- Learned machine learning fundamentals with focus on deep learning techniques using Python and TensorFlow.
- Developed a capstone project: plant disease detection system using leaf images to identify plant diseases.
- Enhanced soft skills through collaborative projects, presentations, and team-based learning activities.
Machine Learning Mentor at Asah led by Dicoding
Dicoding Academy
Remote
- Mentored 45 students in the field of Machine Learning and AI, helping them understand the concepts and techniques of machine learning and AI.
- Assisted students in building their own machine learning projects, from data preparation to model deployment.
- Provided feedback and guidance to students on their machine learning projects, helping them improve their skills and knowledge.
Still Grinding...
Always learning, always growing. The journey continues.
Portfolio
Selected Work
Mobile App
KebunQ
A mobile application that helps home gardeners identify plant diseases in crops like grape, tomato, and cucumber using image recognition technology.
Website
Swistination
A web-based tourism recommendation system for Switzerland using Singular Value Decomposition (SVD) for Collaborative Filtering, integrated with MLOps pipeline featuring CI/CD automation and monitoring.
Streamlit App
Student Performance Prediction App
A Streamlit app that predicts student performance based on various features using machine learning models.