---
title: "Contents"
source: MLOps Guide
source_url: https://github.com/MLOps-Guide/MLOps-Guide
licence: Apache-2.0
domain: data-and-analysis
subdomain: mlops-guide
date_added: 2026-04-25
---

# Contents

A short description of each topic or subtopic.

- __MLOps Theory:__ A brief introduction to the main Principles of MLOps: [Data and Model Versioning](../MLOps/Data/), [Feature Management and Storing](../MLOps/PipelineAutomation/), [Automation of Pipelines and Processes](../MLOps/FeatureStore/),[ CI/CD for Machine Learning](../MLOps/CICDML/) and [Continuous Monitoring of Models](../MLOps/Monitoring/). As well as Common Tools used to address each of those points.

- __Implementations Guide__
     - __Introduction__
        - [__Tools and Project Structure:__](../Structure/project_structure/) Introduction to the project structure and tools that will be used.
        - [__Starting a New Project with Cookiecutter:__](../Structure/starting/) Introduction to  Cookiecutter and how to create a new project based on our template.
    - __Environment__
        - [__Setting Up the IBM Environment with Terraform:__](../Infraestrutura/Terraform/) Using Terraform to set up the IBM Environment via code.
        - [__Managing the deployment space:__](../Infraestrutura/Python/) How to manage IBM's tools with Terraform.

    - __Versioning__
        - [__What is DVC?:__](../Versionamento/) Introduction to DVC, installation and how to setup remote storage.
        - [__Data Versioning:__](../Versionamento/basic_dvc/) Working with DVC to version data and models.
        - [__Working with Pipelines:__](../Versionamento/pipelines_dvc/) Creating and reproducing pipelines for training and evaluating models.

    - __Deployment__
        - [__Deployment with Watson Machine Learning:__](../Deployment) Using Watson ML API to deploy models as an online web service.

    - __CI/CD for Machine Learning__
        - [__Continuous Integration with CML and Github Actions:__](../CICD/cml_testing/) Introduction to CML and GitHub Actions and how to create automatic testing and reportng workflows.
        - [__Continous Delivery with CML, Github Actions and Watson ML:__](../CICD/cml_deploy/) Using CML and GitHub Actions create automatic deployments for every new release.

    - __Monitoring__
        - [__Monitoring with IBM OpenScale:__](../Openscale) Setting up OpenScale environment, creating monitors, evaluating the model and explaining predictions.

    - __Project Workflow__
        - [__Project Workflow:__](../Workflow) Demonstrating how to use the complete pipeline in a development cycle we created with commands and videos.
