Repository containing a portfolio of data science projects completed by me for academic, self-learning, and hobby purposes. Presented in the form of Jupyter notebooks and Python scripts.
Note: The data used in the projects (accessed under the data directory) is for demonstration purposes only.
- Install dependencies using
requirements.txt. - Run notebooks as usual by using a Jupyter Notebook server, VSCode, etc.
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House Prices - Advanced Regression Analysis: A Kaggle competition project predicting house prices using advanced regression techniques. Techniques include feature engineering, handling missing data, and applying various machine learning algorithms to optimize model performance. Tools: Scikit-learn, Pandas, Matplotlib
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Titanic - Machine Learning from Disaster: Classic Kaggle challenge that uses various classification algorithms to predict passenger survival on the Titanic. Emphasis on feature engineering and model selection. Tools: Scikit-learn, Pandas, Seaborn
If you liked what you saw or want to discuss my portfolio, feel free to connect with me via email at olivercareyncl@gmail.com.