Welcome to my Kaggle Data Projects Portfolio!
This repository contains Jupyter notebooks from various Kaggle competitions and datasets. Each project demonstrates my skills in data analysis, feature engineering, machine learning modeling, and result interpretation.
📌 Note: Datasets are not included in this repository. All data used in the notebooks is publicly available on Kaggle and is referenced within each notebook.
Each notebook includes:
- End-to-end data analysis workflow
- Visualizations and key insights
- Model development and evaluation
- Clean, readable, and well-commented code
Example projects:
- Titanic – Binary classification using logistic regression and random forest
- House Prices – Regression with feature engineering and ensemble models
- Customer Churn – Predictive classification with XGBoost
- LLM AI-Generated Text Detection – NLP model training and evaluation
- Python (Pandas, NumPy)
- Jupyter Notebook
- scikit-learn
- Matplotlib, Seaborn
- XGBoost, LightGBM
- NLP tools (e.g., TfidfVectorizer, NLP preprocessing)
This repository serves as a personal portfolio to showcase my data science and machine learning skills. It is intended for learning, sharing, and supporting job applications in the data field.
Feel free to connect with me:
- Linkedin: YI LUO)
- Kaggle: [yiluosjtut]https://www.kaggle.com/yiluosjtut/code