Kaggle-DataQuests

Welcome to my Kaggle Competitions Repository! Here, you will find a collection of Jupyter notebooks showcasing my work and solutions for various Kaggle competitions. Each project is a unique challenge, and I've documented my approach to solving them. Feel free to explore and learn from my code.

If you wish to team up, send me a pm!

List of Projects

1. Titanic: Machine Learning from Disaster

   

   • Description: This project is a classic introduction to Kaggle competitions. It focuses on predicting passenger survival on the Titanic.
   • Notebook:
     • Part 1
       • R
       • Data exploration, data viz, stepwise selection, ROC, logit.
     • Part 2
       • python
       • Feature engineering and tree-based classifiers: XGBoost.

2. Airplane Passenger Satisfaction

   

   • Description: This project showcases dimensionality reduction with PCA for multivariate data visualization and clustering methods.
   • Notebook:
     • python
     • PCA, K-Means, unsupervised learning, plotly.

Notes about Each Project

• Each project directory contains a Jupyter or Quarto notebook with detailed explanations of the data, analysis, feature engineering, and model building process.
• You can find the dataset and any additional resources in the respective project directories.
• If you have any questions or suggestions, feel free to open an issue or reach out to me.

Happy coding, and best of luck with your Kaggle competitions!