fairuztsn/Bike-Supply

Bike Supply (KR) 🚴‍♂️

This project predicts bike supply based on various factors. The features used for prediction include:

• Hour
• Holiday
• Temperature (°C)
• Humidity (%)
• Wind speed (m/s)
• Visibility (10m)
• Dew point temperature (°C)
• Solar Radiation (MJ/m2)
• Rainfall (mm)
• Snowfall (cm)

Getting Started 🏁

These instructions will help you set up and run the project on your local machine.

Prerequisites 🛠️

Make sure you have the following installed on your machine:

• Python (version 3.12.x)
• pip (package installer for Python)
• Git

Clone the Repository 📥

git clone https://github.com/fairuztsn/Bike-Supply.git
cd Bike-Supply

Create a Python Virtual Environment 🌐

It's good practice to use a virtual environment to manage dependencies. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate

If you're using Windows:

./venv/Scripts/activate

Install Dependencies 📦

Install the required Python packages:

pip install -r requirements.txt

Run the Jupyter Notebook 📓

Start the Jupyter notebook to interact with the project:

jupyter notebook

Navigate to the notebooks directory and open the main notebook.

Execute the Run Script 🏃‍♀️

After running the notebook, you might have some additional steps or scripts to execute. If so, run the provided script:

./run

This script runs flask app.