Basketball Playoffs Prediction Project Structure

2024 MEIC - 1st Semester
Course: Machine Learning Grade: TBD

Project developed by:

• Gonçalo Matias
• Tomás Monteiro

1. Project Organization

Project Structure

basketball_playoffs_predictions/
│
├── data/
│   ├── basketballPlayoffs/            # Original data files
│   ├── basketballPlayoffs_cleaned/    # Cleaned Data
│   ├── basketballPlayoffs_model/      # Data for the model development
│   └── Season_11/                     # Data used for the 11th year predictions.
│
└── src/
    ├── notebook_1                     # Data Loading
    ├── notebook_2                     # Data Preprocessing
    ├── notebook_3                     # Exploratory Data Analysis
    ├── notebook_4                     # Feature Engineering
    ├── notebook_5                     # Model Development
    └── notebook_6                     # Model Development for predicitions

2. Key Considerations for Each Notebook

01_data_loading.ipynb

• Introduction to the problem
• Initial import of libraries
• Initial data analysis

02_data_preprocessing.ipynb

• Map categorical values
• Data cleaning
• Outlier treatment

03_exploratory_data_analysis.ipynb

• Analyze trends
• Data visualization
• Create meaningful visualizations

04_feature_engineering.ipynb

• Calculate overall feature creation to simplify the problem
• Document feature creation logic
• Validate feature importance

05_model_development.ipynb

• Split data into training and testing sets to predict year 10
• Create and train models
• Analyze and save results

06_model_evaluation_for_predicitons.ipynb

• Load data for the new year
• Add previously calculated features (overalls)
• Develop and train the model for competition