This notebook uses machine learning algorithms to get the best accuracy of predictions for who survived the sinking of the Titanic given the attributes in the dataset.

• Install Python 3.12.2
  • Run python --version to ensure you have the correct version
• and/or create a Python virtual environment with Python 3.12.2
  • If you have the right python version, simply create a new python virtual environment using the following CLI python -m venv /path/to/new/virtual/environment (I prefer placing the virtual environment inside the project folder so that VS code can automatically detect the right kernel)
• Activate your virtual environment
• Once your environment is activated, navigate to the folder containing the project/repo files and run the following command in the terminal to install all required packages:
  • pip install -r requirements.txt
• In VS Code, open the "Titanic - Abdullah.ipynb" file and ensure the right kernel is connected
• To be able to view the decision tree in the output, you will need to install the graphviz library.
  • I used graphviz version 10.0.1 (post installation you can check the version and correct installation by running dot -V in the terminal)
  • I simply used scoop on windows to install graphviz. You can use brew on Mac/Linux to install graphviz.
• Make sure that you have the python and jupyter extention installed on VS Code.

You can compare my implementation of the notebook (Titanic - Abdullah.ipynb) with that of Claudia's and Iemejia's side-by-side.