The goal of Zumel/Mount: Practical Data Science with R is to teach, through guided practice, the skills of a data scientist. We define a data scientist as the person who organizes client input, data, infrastructure, statistics, mathematics and machine learning to deploy useful predictive models into production. Our plan to teach is to: Order the […]
Data Science, Machine Learning, and Statistics: what is in a name?
Setting expectations in data science projects
Data science project planning
The intent of Practical Data Science with R is to be a useful concrete example of how to do data science. We limited ourselves to working in R not because a data scientist can choose to work exclusively in R (they can not), but to limit the number of external tools and considerations we had to discuss before getting to the actual examples. To use our book you will need to work the examples (and this can be as shallow as cutting and pasting code or as deep as trying variations after the data has been loaded)
See on www.r-bloggers.com