AutoMLCronPipeline is a Python-based solution designed for automating machine learning workflows. It integrates continuous deployment and training strategies without relying on cloud-based services, focusing on cron jobs for scheduling tasks.
- Continuous Deployment: Seamless integration for ML model deployment.
- Cron-based Scheduling: Utilize cron jobs for periodic task execution.
- Machine Learning Automation: Streamline the process of training and updating models.
- Cloudless Architecture: Operate independently of cloud platforms for enhanced privacy and control.
- UNIX-based System: Essential for cron job execution.
- Python Environment: Ensure Python is installed with necessary libraries for machine learning and automation tasks.
- Network Access: For retrieving data and interacting with any APIs if required.
Details on how to set up and use the pipeline will be provided, including setup instructions, configuration details, and execution steps.
Create a virtual environment using:
conda env create -f environment.yml -n auto_ml
conda activate auto_ml
# or
python3.9 -m venv auto_ml
pip install -r requirements.txt
Test execution of training and check if log files are updated:
python src/main.py
This project is licensed under the MIT License.