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 Streamlit-based AutoML-style machine learning experiment platform that supports CSV upload, automatic preprocessing, classification and regression model comparison, model leaderboard, visualization, markdown report download, single-row prediction, and best model export.

GitHub Repo: https://github.com/Lovis-Ghost/automl-experiment-lab

Key Features:

• CSV upload and built-in sample datasets
• Automatic numeric and categorical feature preprocessing
• Classification and regression model training
• Model leaderboard based on F1-score or R2 score
• Best model saving with metadata
• Markdown experiment report download
• Single-row prediction demo

Tech Stack: Python, Streamlit, pandas, NumPy, scikit-learn, Matplotlib, Joblib

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

• Building portfolio projects that combine data analysis, machine learning pipelines, model evaluation, and user-facing Streamlit interfaces
• Improving practical machine learning workflows, including preprocessing, classification, regression, evaluation metrics, and model export
• Developing AI-assisted applications and agent-style workflows using LLM APIs with clear fallback behavior and readable documentation
• Strengthening pandas, NumPy, scikit-learn, visualization, and Git/GitHub skills through complete, documented projects
• Practicing algorithms and data structures to support technical interviews and stronger software development fundamentals
• Connecting academic AI research topics with practical projects, especially trustworthy AI, hallucination, RAG, and factual consistency

• GitHub: @Lovis-Ghost
• Currently open to AI, Data Science, Machine Learning, and AI Agent internship opportunities