About the reviewers

Margriet Groenendijk is a data scientist and developer advocate for IBM. She has a background in climate research, where, at the University of Exeter, she explored large observational datasets and the output of global scale weather and climate models to understand the impact of land use on climate. Prior to that, she explored the effect of climate on the uptake of carbon from the atmosphere by forests during her PhD research at the Vrije Universiteit in Amsterdam.

Now adays, she explores ways to simplify working with diverse data using open source tools, IBM Cloud, and Watson Studio. She has experience with cloud services, databases, and APIs to access, combine, clean, and store different types of data. Margriet uses time series analysis, statistical data analysis, modeling and parameter optimisation, machine learning, and complex data visualization. She writes blogs and speaks about these topics at conferences and meetups.

va barbosa is a developer advocate for the Center for Open-Source Data & AI Technologies, where he helps developers discover and make use of data and machine learning technologies. This is fueled by his passion to help others, and guided by his enthusiasm for open source technology.

Always looking to embrace new challenges and fulfill his appetite for learning, va immerses himself in a wide range of technologies and activities. He has been an electronic technician, support engineer, software engineer, and developer advocate.

When not focusing on the developer experience, va enjoys dabbling in photography. If you can't find him in front of a computer, try looking behind a camera.