Titanic scikit-learn demo

Jupyter Notebook for Data Science Presentation. This Notebook shows examples of Feature Engineering and Hyperparameter tuning.

The Kaggle Titanic Problem

• https://www.kaggle.com/c/titanic/data

Video: Dive Into Data Science and Build your First ML Model – With All Star Rhea

• Tuesday, 8:30 AM PST on 15th March 2022
• https://www.youtube.com/watch?v=ToHp0hrNheI

Dependencies

Install pip3 and python3 and then the necessary packages from requirements.txt

python -m pip install -r requirements.txt

I like to create a python virtual environment for individual projects. This is a resource I refer to frequently.

Once you have pip3 installed locally, install the virtualenv package with

python3 -m pip install --user virtualenv

Then go ahead and create a virtual environment which will be saved in a directory called 'env' within your current directory, as follows

python3 -m venv env

Note: You should exclude your virtual environment directory from your version control system using .gitignore or similar.

Activate the virtual environment by

source env/bin/activate

And to deactivate,

deactivate

Once you are within the active virtual environment you can install the dependent packages from the requirement.txt file in this repository by,

python3 -m pip install -r requirements.txt

In case you were wondering, I created the requirement.txt file like this,

python3 -m pip freeze