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https://github.com/tushar2704/audiophile-insights
Audiophile-Insights
https://github.com/tushar2704/audiophile-insights
streamlit-tushar2704
Last synced: 19 days ago
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Audiophile-Insights
- Host: GitHub
- URL: https://github.com/tushar2704/audiophile-insights
- Owner: tushar2704
- Created: 2023-09-22T13:40:39.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-09-24T16:01:27.000Z (over 1 year ago)
- Last Synced: 2024-05-11T05:53:45.143Z (8 months ago)
- Topics: streamlit-tushar2704
- Homepage: https://tushar-aggarwal.com
- Size: 6.84 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Audiophile-Insights
Welcome to Audiophile-Insights, a comprehensive project for analyzing and predicting global headphone sales using machine learning techniques. This repository contains all the code, data, and documentation related to this project.
## Project Overview
The objective of Audiophile-Insights is to provide valuable insights into the global headphone market and to predict sales trends. This project leverages machine learning and data analysis techniques to achieve this goal.
## Table of Contents
- [Project Overview](#project-overview)
- [Getting Started](#getting-started)
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Usage](#usage)
- [Data](#data)
- [Analysis](#analysis)
- [Results](#results)
- [Contributing](#contributing)
- [License](#license)
## Getting Started
### Prerequisites
- [Python](https://www.python.org/) (>=3.7)
- [Jupyter Notebook](https://jupyter.org/) (for interactive data analysis)
- [Dependencies](#installation)
### Installation
1. Clone this repository:
```shell
git clone https://github.com/your-username/Audiophile-Insights.git
cd Audiophile-Insights
```
2. Install the required dependencies:
```shell
pip install -r requirements.txt
```
## Usage
- [Detailed Usage Instructions](docs/usage.md) (if necessary)
## Data
- [Data Sources](docs/data-sources.md) - Information about the data used in this project.
- [Data Preprocessing](notebooks/data-preprocessing.ipynb) - Jupyter Notebook for data cleaning and preprocessing.
## Analysis
- [Exploratory Data Analysis (EDA)](notebooks/eda.ipynb) - Jupyter Notebook for exploring the dataset.
- [Time Series Forecasting](notebooks/time-series-forecasting.ipynb) - Jupyter Notebook for sales predictions.
## Results
- [Summary of Findings](docs/results.md) - Key insights and findings from the analysis.
- [Interactive Dashboard](link-to-dashboard) - Link to an interactive dashboard (if available).
## Contributing
We welcome contributions from the community. To contribute, please follow our [Contribution Guidelines](CONTRIBUTING.md).
## License
This project is licensed under the [MIT License](LICENSE). Feel free to use, modify, and distribute the code and content within the terms of this license.