Goal: Create a new plugin for integrating Jenkins with one of Machine Learning tools (e.g. Jupyter Python, TensorBoard, or Sacred)
The main goal of this project is integrating Machine Learning workflow including Data preprocessing, Model Training, Evaluation and Prediction with Jenkins build tasks. This plugin will be capable of executing code fragments via IPython kernel as currently supported by Jupyter Notebook. Version control will be handled as an added advantage of this project.
An IPython plugin with pipeline compatible
Improved config.jelly for the plugin
File parsers for ipynb, py and text(containing python code) files
Code segment extractor
Implement a code editor
Output console with static visual components
The community bonding period is all about, well, community bonding. Rather than jumping straight into coding, I’ve got some time to learn about Jenkins’s processes - release and otherwise - developer interactions, codes of conduct, etc.
Design and implement code extractor
Multiple language kernel support
Implement Visual generator for the results
Integrate whole previous work and testing
Git integration for code segments (optional)
User documentation and examples