2023-07-28 –, 32-123
We present our package and book that we’ve developed to write Julia for Data Science Book. Unlike many other books, our book considers functions are first class citizens and is fully (re)built with CI. We discuss how to develop a code of conduct for communication guidelines and a workflow for coauthoring together using GitHub features such as pull request and issues as project management tools.
Like many people before us, we started working on a book only to realize that the tools were not helpful enough.
So, as a proper case of yak shaving, we first created a software package to write books.
We will present our package and book that we've developed to write Julia for Data Science Book.
We write this book for researchers from all fields, while keeping robust software development practices in mind.
Unlike many other books, our book considers functions are first class citizens and is fully (re)built with CI.
And, finally, we'll discuss how to develop a code of conduct for communication guidelines and a workflow for coauthoring together using GitHub features such as pull request, issues and projects as software project management tools.
Associate Professor and Researcher of the Department of Computer Science at Universidade Nove de Julho - UNINOVE located in São Paulo - Brazil. Director of Education and Training at Pumas-AI.
Teaches undergraduate and graduate courses in Data Science, Statistics, Bayesian Statistics, Machine Learning and Deep Learning using Julia, R, Python, and Stan. Contributor to Julia, R and Stan ecosystems.
Researches, publishes and advises PhD candidates on topics about Bayesian Statistical Modeling and Machine Learning applied to Decision Making.
Coauthor of Julia Data Science book. Directs the development of education and training materials for Pumas users in Julia. Member of the Stan Governing Body - SGB. Member of the Turing.jl Developer Team. Certified RStudio Tidyverse Instructor.