Master of Artificial Intelligence student at Universiti Kebangsaan Malaysia, preparing for AI, Data Science, Machine Learning, and AI Agent internship opportunities.
I am currently building practical AI and data projects using Python, Streamlit, pandas, scikit-learn, Git, GitHub, and LLM APIs, while strengthening my foundation in algorithms, data structures, and machine learning.
- 🎓 Master of Artificial Intelligence student at Universiti Kebangsaan Malaysia
- 💡 Interested in AI Agents, Machine Learning, Data Science, and practical problem solving
- 📊 Building hands-on projects that connect data analysis, model training, deployment, and reporting
- 🧠 Developing my understanding of algorithms, data structures, and research-based AI topics
- 🚀 Preparing for internship roles where I can learn, contribute, and grow professionally
An end-to-end Streamlit application for automated CSV/Excel dataset analysis, data quality assessment, AI-assisted insights, baseline machine learning training, model download, prediction demo, and Markdown/Word/PDF report generation.
Live Demo: https://ai-data-analysis-ml-agent.streamlit.app
GitHub Repo: https://github.com/Lovis-Ghost/ai-data-analysis-ml-agent
Key Features:
- Automated CSV/Excel dataset profiling and data quality checking
- Smart column detection for numerical, categorical, and ID-like features
- Optional OpenAI/Gemini AI-assisted insights with fallback support
- Baseline classification and regression model training using scikit-learn Pipelines
- Model evaluation, best model selection, model download, and prediction demo
- Markdown, Word, and PDF report export
- Modular Python project structure with example dataset, screenshots, and technical documentation
Tech Stack: Python, Streamlit, pandas, NumPy, scikit-learn, matplotlib, OpenAI API, Gemini API, python-docx, ReportLab
A machine learning practice project focused on predicting customer churn using data analysis and classification techniques.
- Focus: data preprocessing, exploratory data analysis, model training, and evaluation
- Tools: Python, pandas, scikit-learn
- Goal: understand the full workflow of a beginner-friendly machine learning project
An academic literature review project exploring hallucination in large language models, especially in summarization and citation-grounded generation.
- Focus: literature search, paper screening, candidate paper matrix, and research notes
- Topics: hallucination detection, mitigation, RAG, faithfulness, and factual consistency
- Goal: build research understanding for trustworthy AI and academic summarization
A learning practice project for improving problem-solving skills through algorithms and data structures.
- Focus: Python programming, basic algorithms, data structures, and coding exercises
- Topics: arrays, strings, searching, sorting, and problem-solving patterns
- Goal: strengthen programming fundamentals for technical interviews and AI development
- Python programming and modular project development
- Machine learning fundamentals and model evaluation
- Data analysis with pandas and visualization tools
- Streamlit app development and deployment
- LLM-assisted applications and AI agent workflows
- Git, GitHub, and portfolio project documentation
- Algorithms and data structures
- GitHub: @Lovis-Ghost
- Currently open to AI, Data Science, Machine Learning, and AI Agent internship opportunities