Welcome to my personal laboratory for AI and Data Science. This repository serves as a documentation of my "ngulik" (hands-on exploration) sessions, moving beyond theory into practical application.
- Bridge the Gap: Moving from 4th-semester theory at Telkom University to real-world data application.
- Skill Building: Mastering Python libraries (Pandas, NumPy, Matplotlib) and Machine Learning workflows.
- Transparency: Documenting the process, errors, and breakthroughs of every tutorial and experiment.
- Spotify Data Analysis: - Status: In Progress 🚧
- Focus: Analyzing track trends and artist popularity using the Simplilearn framework.
- Tools: Python, Pandas, Seaborn.
- Languages: Python, SQL (PostgreSQL)
- Environment: Google Colab, Kaggle
- Key Libraries: Pandas, Scikit-Learn, Matplotlib
“Done is better than perfect.” – Documenting my journey one commit at a time.