# Topic: Machine Learning Engineering

Machine learning is useless unless the models are being used. Machine learning
engineering is the discipline of operationalizing those models by building
scalable APIs and systems around them. My articles about machine learning
engineering can be found here:

- [Machine Learning Deployment: <br>Return Actions, Not Scores](/blog/machine-learning-return-actions-not-scores/)
- [Using Scikit-learn Pipelines with Pandas Dataframes](/blog/using-sklearn-pipelines-with-pandas-dataframes/)
- [Computing Machine Learning Features in Real-time](/blog/realtime-machine-learning-features/)
- [Machine Learning Deployment: Shadow Mode](/blog/machine-learning-deployment-shadow-mode/)