Chris Moradiin97 ThingsFocus on Maintainability and Break Those ETL Tasks UpWhen writing ETLs, we should ensure others are able to support and extend our work by breaking complex tasks into a chain of simple ones.Jul 11, 2019Jul 11, 2019
Chris MoradiTwo New Stitch Fix Blog PostsMaintainable ETLs & Non-Inferiority ExperimentsMay 21, 2019May 21, 2019
Chris MoradiinTowards Data ScienceBuilding Prediction APIs in Python (Part 4): Decoupling the Model and APIIn the last part, we looked at automated testing with pytest to verify that our API is correctly scoring the model. In this post, we’ll…Feb 18, 2018Feb 18, 2018
Chris MoradiinTowards Data ScienceBuilding Prediction APIs in Python (Part 3): Automated TestingIn the last post, we improved the error handling of our prediction API and considered the nuanced decision about which records we should…Feb 7, 2018Feb 7, 2018
Chris MoradiinTowards Data ScienceBuilding Prediction APIs in Python (Part 2): Basic Error HandlingIn the initial series post, we created a simple API to score a Scikit-Learn random forest classifier built on the iris dataset. In this…Feb 4, 20182Feb 4, 20182
Chris MoradiinTowards Data ScienceBuilding Prediction APIs in Python (Part 1): Series Introduction & Basic ExampleOk, so you’ve trained a model, but now what? All that work is meaningless if no one can use it. In some applications, you can simply create…Jan 31, 20189Jan 31, 20189
