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About the Book
Hey there, data scientist! Have you found yourself struggling with your compute environment, such as package conflicts, this cryptic term called "environment variables", this weird concept called "containers", and technology terms that feel like an entire stack of things to learn? How about being lost amongst your multitude of projects, and not being able to get organized? This book, a linearized form of my freely available knowledge base, will give you a concise and practical guide to getting up-to-speed and organized, to help you do your best data science work.
The content in this book has been battle-tested since 2013 when I first switched over from bench science to computational science. You'll benefit from my distilled experience, where I learned all the hard lessons that come from not applying "best data science practices" to my projects, so you can avoid the same mistakes. You'll also benefit from the countless number of times I have guided newcomer colleagues and data practitioners to data science on getting their systems set up. You'll see the backing philosophies, the "whys" that explain why we ought to do certain things a certain way, as well as manifestations of those "whys".
End the struggle with getting your computer to do what you want. Gain full control over it instead. Come and learn how!
About the Author
As Principal Data Scientist at Moderna Eric leads the Data Science and Artificial Intelligence (Research) team to accelerate science to the speed of thought. Prior to Moderna, he was at the Novartis Institutes for Biomedical Research conducting biomedical data science research with a focus on using Bayesian statistical methods in the service of discovering medicines for patients. Prior to Novartis, he was an Insight Health Data Fellow in the summer of 2017 and defended his doctoral thesis in the Department of Biological Engineering at MIT in the spring of 2017.
Eric is also an open-source software developer and has led the development of pyjanitor, a clean API for cleaning data in Python, and nxviz, a visualization package for NetworkX. He is also on the core developer team of NetworkX and PyMC. In addition, he gives back to the community through code contributions, blogging, teaching, and writing.
His personal life motto is found in the Gospel of Luke 12:48.