- This project aims to predict the likelihood of a passenger surviving the Titanic shipwreck
- Preprocessing techniques to deal with both categorical and numerical data types
- Model is trained on features such as age, sex, class, etc using a Linear Classifier provided by TensorFlow
- Performance is evaluated using the testing data, and the accuracy metric is printed as an outcome
- Python 3.x
- TensorFlow
- Pandas
- Numpy
- Matplotlib
- Age
- Sex
- Number of siblings and spouses aboard
- Number of parents and children aboard
- Passenger class
- Deck
- Embarkation town
- Alone status
- The label for prediction is whether the passenger survived or not
- The dataset is split into training (train.csv) and testing (eval.csv) data
- Clone the repo:
https://github.com/williamlin6803/Survival.git
- Run pip install -r requirements.txt to install dependencies
- Execute the Python script: python titanic_survival_prediction.py
- The model achieves an accuracy of 78% on the test data
- Implement more sophisticated models that uses other Machine Learning Techniques such as Random Forests or Neural Networks for better accuracy