If you type 'unit test' into your favorite search engine, you will receive a lot of information for Software Engineering, but very little guidance for Data Science code. In Data Science, the small piece of code that you want to test also needs to take in data, training a model, or evaluating a model, but all of these steps are complicated and consist of many smaller units. In this talk, Dr. Nile Wilson will share her Software Engineering best practices for testing Data Science Code and some of the common scenarios for data, like mocking calls or mocking data. This talk is for anyone bridging the gap between Software Engineering and Data Science, anyone in MLOps, or anyone productionalizing data.
Dr. Nile Wilson is a Data Scientist 2 in Industry Solutions Engineering at Microsoft, focused on developing and implementing Machine Learning solutions for enterprise customers. She has worked with interdisciplinary teams across various industries to develop production-ready data science solutions driving business impact. From media & communications to healthcare, Nile combines engineering best practices with data science principles and effective communication to collaboratively build lasting solutions.