# MLOps

## MLOps Playbook

- [Overview](https://playbooks.equalexperts.com/mlops-playbook/overview.md)
- [Key terms](https://playbooks.equalexperts.com/mlops-playbook/overview/key-terms.md)
- [What is MLOps](https://playbooks.equalexperts.com/mlops-playbook/what-is-mlops.md)
- [Principles](https://playbooks.equalexperts.com/mlops-playbook/principles.md)
- [Solid data foundations](https://playbooks.equalexperts.com/mlops-playbook/principles/solid-data-foundations.md)
- [Provide an environment that allows data scientists to create and test models](https://playbooks.equalexperts.com/mlops-playbook/principles/provide-an-environment-that-allows-data-scientists-to-create-and-test-models.md)
- [A machine learning  service is  a product](https://playbooks.equalexperts.com/mlops-playbook/principles/a-machine-learning-service-is-a-product.md)
- [Apply continuous delivery](https://playbooks.equalexperts.com/mlops-playbook/principles/apply-continuous-delivery.md)
- [Evaluate and monitor  algorithms throughout their lifecycle](https://playbooks.equalexperts.com/mlops-playbook/principles/evaluate-and-monitor-algorithms-throughout-their-lifecycle.md)
- [MLOps is a team effort](https://playbooks.equalexperts.com/mlops-playbook/principles/mlops-is-a-team-effort.md)
- [Practices](https://playbooks.equalexperts.com/mlops-playbook/practices.md)
- [Collect performance data](https://playbooks.equalexperts.com/mlops-playbook/practices/collect-performance-data.md)
- [Ways of deploying your model](https://playbooks.equalexperts.com/mlops-playbook/practices/ways-of-deploying-your-model.md)
- [How often do you deploy a model?](https://playbooks.equalexperts.com/mlops-playbook/practices/how-often-do-you-deploy-a-model.md)
- [Keep a versioned model repository](https://playbooks.equalexperts.com/mlops-playbook/practices/keep-a-versioned-model-repository.md)
- [Measure and proactively evaluate quality of training data](https://playbooks.equalexperts.com/mlops-playbook/practices/measure-and-proactively-evaluate-quality-of-training-data.md)
- [Testing through the ML pipeline](https://playbooks.equalexperts.com/mlops-playbook/practices/testing-through-the-ml-pipeline.md)
- [Business impact is more than just accuracy - understand your baseline](https://playbooks.equalexperts.com/mlops-playbook/practices/business-impact-is-more-than-just-accuracy-understand-your-baseline.md)
- [Regularly monitor your model in production](https://playbooks.equalexperts.com/mlops-playbook/practices/regularly-monitor-your-model-in-production.md)
- [Monitor data quality](https://playbooks.equalexperts.com/mlops-playbook/practices/monitor-data-quality.md)
- [Automate the model lifecycle](https://playbooks.equalexperts.com/mlops-playbook/practices/automate-the-model-lifecycle.md)
- [Create a walking skeleton/steel thread](https://playbooks.equalexperts.com/mlops-playbook/practices/create-a-walking-skeleton-steel-thread.md)
- [Appropriately optimise models for inference](https://playbooks.equalexperts.com/mlops-playbook/practices/appropriately-optimise-models-for-inference.md)
- [Explore](https://playbooks.equalexperts.com/mlops-playbook/explore.md)
- [Pitfalls (Avoid)](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid.md)
- [User Trust and Engagement](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/user-trust-and-engagement.md)
- [Explainability](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/explainability.md)
- [Avoid  notebooks in production](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/avoid-notebooks-in-production.md)
- [Poor security practices](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/poor-security-practices.md)
- [Don’t treat accuracy as the only or even the best way to  evaluate your algorithm](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/dont-treat-accuracy-as-the-only-or-even-the-best-way-to-evaluate-your-algorithm.md)
- [Use machine learning judiciously](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/use-machine-learning-judiciously.md)
- [Don’t forget to understand the at-inference usage profile](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/dont-forget-to-understand-the-at-inference-usage-profile.md)
- [Don’t make it difficult for a data scientists to access data or use the tools they need](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/dont-make-it-difficult-for-a-data-scientists-to-access-data-or-use-the-tools-they-need.md)
- [Not taking into consideration the downstream application of the model](https://playbooks.equalexperts.com/mlops-playbook/pitfalls-avoid/not-taking-into-consideration-the-downstream-application-of-the-model.md)
- [Contributors](https://playbooks.equalexperts.com/mlops-playbook/contributors.md)