MLOps Codex

MLOps Codex is a Python package designed to facilitate interaction with MLOps platforms. Datarisk MLOps is a comprehensive platform for managing Machine Learning (ML) models, enabling users to seamlessly train, deploy, and monitor their models. To utilize the MLOps API, users must host their Python scripts and notebooks within the MLOps Codex environment.

Installation

The package is available on PyPI and can thus be installed with:

pip install datarisk-mlops-codex

Getting started

Check our guide on how to use MLOps Codex to manage models

• Starters Guide
  • Connecting to MLOps
  • Preprocessing data with MLOps Codex
  • Training your model
  • Connecting to a Data Source
  • Deploying to production

Beside that several notebooks gives examples of how to use MLOps-Codex to manage, deploy and other package functionalities. You can find it at:

Package Reference

Gives an overview of all objects, functions and methods. All classes and functions exposed in mlops_codex.* namespace are public.

Docs:

• mlops_codex package
  • Modules
    • Base module
    • Model module
    • Training module
    • External Monitoring module
    • DataSource module
    • Preprocessing module
    • Pipeline module
    • Dataset Module
    • Logging module
    • Exceptions module

Development Version

If you want to track the development version of the package, you can install it from the git repo:

pip install git+https://github.com/datarisk-io/mlops_codex.git@master

Maintainers

• Manuella Dias Cruz: ManuDiasCruz

• Jonathan Carvalho: johnrc90

• Luís Henrique: henrique-lh

Indices and tables

• Index

• Module Index

• Search Page