Welcome to the DA_2023_Project repository! This repository contains the code and resources for our data analysis project for the year 2023.

The DA_2023_Project is a data analysis project that aims to analyze a specific dataset or problem using various data analysis techniques. The goal of this project is to gain insights, draw meaningful conclusions, and present the findings to the intended audience.

The dataset consists of data collected from heavy Scania trucks in everyday usage. The system in focus is the Air Pressure system (APS) which generates pressurized air that is utilized in various functions in a truck, such as braking and gear changes. The datasets’ positive class consists of component failures for a specific component of the APS system. The negative class consists of trucks with failures for components not related to the APS. The data consists of a subset of all available data, selected by experts.

The training set contains 60000 examples in total of which 59000 belong to the negative class and 1000 positive class. The test set contains 16000 examples. There are 171 attributes per record

Link to Dataset

• Installation
• Usage
• Contributing
• License
• Contact

To get started with this project, follow the steps below:

1. Clone the repository:

   git clone https://github.com/VPLEV23/DA_2023_Project.git

2. Install the required dependencies:

   pip install -r requirements.txt
   

To use the code in this repository, follow these steps:

1. Navigate to the project directory:

   cd DA_2023_Project

2. Run the main script or application:

   jupyter-notebook

3. Follow any instructions or prompts provided by the code.
4. Review the results or outputs generated by the analysis.

We welcome contributions to improve the DA_2023_Project repository. If you would like to contribute, please follow these guidelines:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and test them thoroughly.
4. Submit a pull request, clearly describing the changes you've made.
5. Wait for the maintainers to review your pull request. We appreciate your patience!

This project is licensed under the MIT License. You are free to use, modify, and distribute this code as per the terms of the license.

Name: Vlad Bulhakov

GitHub: @VPLEV23
Email: [email protected]

Name: Danylo Savchak

GitHub: @Savchak00
Email: [email protected]

Name: Artem Chernobrovkin

GitHub: @Watfireme
Email: [email protected]