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  1. Quantitative-Investing-Multiple-Technical-Indicator-Trading-Strategy Quantitative-Investing-Multiple-Technical-Indicator-Trading-Strategy Public

    This project uses Python to create an optimally weighted stock portfolio by combining 7 common technical indicators, generating trading signals, backtesting the strategy, and aiming to outperform t…

    Jupyter Notebook 4 1

  2. 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 2

  3. 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 1

  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. 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

  6. 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 …