Airline-Passenger-Satisfaction

Airline-Customer-Model — Machine Learning Project on: Scikit-learn / Pandas / Matplotlib / Seaborn

Machine learning project focused on analyzing airline passenger satisfaction. The model explores factors influencing satisfaction levels using Scikit-learn, Pandas, Matplotlib, and Seaborn. The results will help identify key areas for improvement and predict satisfaction based on variables such as gender, age, and class of service. The project aims to enhance overall passenger experience.

Stack:

• Python
• NumPy
• Pandas
• Scikit-learn
• Matplotlib
• Seaborn

Additional libraries are specified in the requirements.txt file.

Project Setup on Windows

- Installing the Stack

To begin, install: Python
Links are provided to the latest version of the tools.

- Cloning a Project from GitHub

Create a root directory on your computer, then open it in your code editor or terminal.
Next, write this command into the command line:

git clone https://github.com/S0fft/Airline-Passenger-Satisfaction.git .

You will see the project files appear in your directory.

- Creating a Virtual Environment

Create a virtual environment:

python -m venv .venv

And activate it:

.venv\Scripts\Activate

- Installing the Requirements

Next, install packages:

python.exe -m pip install --upgrade pip

pip install -r requirements.txt

- Running the Models

Open Jupyter Notebook using the command:

jupyter notebook

In the opened interface, select the desired notebook. In the menu at the top of the page, choose Cell → Run All.

Project Setup on Unix-Like Systems

These commands do the same thing as described above but only on Unix systems:

- Installing the Stack

Install: Python | PostgreSQL
Link are provided to the latest version of the tools.

- Cloning a Project from GitHub

Create a root directory on your computer, then open it in your code editor or terminal.
Next, write this command into the command line:

git clone https://github.com/S0fft/Airline-Passenger-Satisfaction.git .

You will see the project files appear in your directory.

- Creating a Virtual Environment

python3 -m venv ./venv

source ./venv/bin/activate

- Installing the Requirements

python3 -m pip install --upgrade pip

pip install -r requirements.txt

- Running the Models

Open Jupyter Notebook using the command:

jupyter notebook

In the opened interface, select the desired notebook. In the menu at the top of the page, choose Cell → Run All.