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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

  1. create a new virtual environment with python ^3.11 and activate it

  2. install mloptiflow:

pip install mloptiflow
  1. 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>
  1. cd into your project directory:
cd <your-project-name>
  1. 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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