Dynamic MLOps Framework with Integrated CLI for Automated ML Project Inception, Kafka-Driven Real-Time Model Monitoring, and Adaptive Canary Deployment Architectures
Project description
MLOPTIFLOW
Dynamic MLOps Framework with Integrated CLI for Automated ML Project Inception, Kafka-Driven Real-Time Model Monitoring, and Adaptive Canary Deployment Architectures
Installation
-
create a new virtual environment with python ^3.11 and activate it
-
install mloptiflow:
pip install mloptiflow
- initialize a new project and choose a name and paradigm (currently supported paradigms are:
tabular_regression,tabular_classification,demo_tabular_classification)[demo ones are just a minimalistic examples of the paradigm]:
mloptiflow init <your-project-name> --paradigm=<paradigm-name>
cdinto your project directory:
cd <your-project-name>
- install dependencies:
poetry install
or if using pip:
pip install -r requirements.txt
Usage
- TBA
Support
- TBA
Roadmap
- TBA
Contributing
- TBA
License
MIT
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