https://github.com/jomaminoza/data-science-docker-base
Dockerized Project Base Template for Data Science Projects
https://github.com/jomaminoza/data-science-docker-base
annotation-tool bioinformatics computer-vision data-science doccano docker docker-compose geospatial natural-language-processing speech-recognition template-project time-series-analysis
Last synced: 5 months ago
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Dockerized Project Base Template for Data Science Projects
- Host: GitHub
- URL: https://github.com/jomaminoza/data-science-docker-base
- Owner: JomaMinoza
- License: mit
- Created: 2024-09-05T10:19:18.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-12-16T21:12:47.000Z (over 1 year ago)
- Last Synced: 2025-07-01T12:03:32.838Z (12 months ago)
- Topics: annotation-tool, bioinformatics, computer-vision, data-science, doccano, docker, docker-compose, geospatial, natural-language-processing, speech-recognition, template-project, time-series-analysis
- Language: Dockerfile
- Homepage:
- Size: 23.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
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README
# Data Science Docker Base
This repository provides Docker Compose configurations and pre-built Docker images tailored for data science projects. The images come with essential libraries and tools for various domains, including visualization, data processing, NLP, computer vision, time series, and geospatial analysis. Additionally, the project includes Doccano for annotation, making it a complete toolkit for different data science tasks.
## Features
- **Pre-configured Docker Compose** setup for easy environment management.
- **Comprehensive toolset**: Packages for:
- Visualization
- Data processing
- Natural Language Processing
- Computer Vision
- Time series
- Geospatial
- **Doccano integration** for easy annotation of text, images, and more.
- Ready-to-use Docker images for Jupyter Notebook and other data science tools.
## Getting Started
### Prerequisites
Before you begin, ensure you have the following installed on your local machine:
- [Docker](https://docs.docker.com/get-docker/)
- [Docker Compose](https://docs.docker.com/compose/install/)
### Installation
1. Clone the repository:
```bash
git clone https://github.com/jomaminoza/data-science-docker-base.git
cd data-science-docker-base
```
2. Build the Docker containers using docker-compose:
```bash
docker-compose build
```
3. Start the containers:
```bash
docker-compose up
```
4. After starting the containers, you can access Jupyter Notebook by visiting the following URL in your browser:
```bash
http://localhost:5000
```
(The default port and URL may vary depending on your configuration.)
### Accessing the Jupyter Notebook
Once the containers are running, Jupyter Notebook will be available in your browser. Simply open the URL provided in the console output.
### Stopping the Containers
To stop the running containers, press CTRL+C in the terminal where the containers are running or use:
```bash
docker-compose down
```