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1. Machine-Learning-Models-for-Stock-Options Machine-Learning-Models-for-Stock-Options Public

   The goal of this project is to find the best regression and classification models using European call option pricing data on the S&P 500 to predict "Value" and "BS" with maximum out-of-sample r squ…

   Jupyter Notebook 3

2. Random-Forest-Rule-Extraction Random-Forest-Rule-Extraction Public

   The provided script extracts rules from each decision tree within a trained Random Forest model and aggregates them into a readable format. These rules can then be utilized independently for classi…

   Jupyter Notebook 2

3. Comprehensive-Feature-Predictive-Power-Analysis-and-Selection Comprehensive-Feature-Predictive-Power-Analysis-and-Selection Public

   A comprehensive analysis pipeline using exploratory data analysis (EDA), statistical metrics (IV, WOE, PSI), and LightGBM with SHAP values to evaluate, visualize, and select optimal features (in th…

   Jupyter Notebook

4. Interactive-Website-and-Dashboard-for-NBA-Data Interactive-Website-and-Dashboard-for-NBA-Data Public

   A comprehensive Plotly Dash dashboard and interactive website analyzing the factors influencing NBA team wins.

   Jupyter Notebook

5. Marketing-Analytics-Research-Study-for-Netflix Marketing-Analytics-Research-Study-for-Netflix Public

   An analytical study on Netflix's decline in total subscribers, utilizing existing data and an online questionnaire to understand user preferences and segment audiences. Our analysis led to various …

6. NLP-Analysis-for-Disneyland-Reviews NLP-Analysis-for-Disneyland-Reviews Public

   An NLP analysis (topic modeling and sentiment analysis) of Disneyland reviews for 3 of its branches (California, Hong Kong, and Paris).

   Jupyter Notebook