Book Review: Machine Learning with R
Summary: Mixes code and concepts very well. Consistent format between each topic chapter. Great for R newbies and R pros looking for insight into a specific model or package.
Summary: Mixes code and concepts very well. Consistent format between each topic chapter. Great for R newbies and R pros looking for insight into a specific model or package.
Summary: Dean Wampler from Lightbend presented at the Direct Supply MSOE offices on Tuesday, 4/5/2016. Dean covered a high-level overview of Spark and its benefits (business logic is focus of code and it’s faster). Those wanting to learn more should pick up Learning Spark at O’Reilly books.
Summary: Building a repository of good report components helps you quickly assemble reports that work. Typical things to watch for are: Opening statements, summary sections, key takeaways, useful dimensions and metrics, and recommendations.
Summary: The tm and lsa packages provide you a way of manipulating your text data into a term-document matrix and create new, numeric features. The ngram package lets you find frequent word patterns (e.g. “The cow” is a bi-gram or 2-gram; “The cow said” is a tri-gram or 3-gram). Lastly, for a quick visualization (though […]
I’m on a bit of a reading kick as of late so I wanted to compile a short list of some useful and free data mining / data science books. Most are of a technical nature and come from academia Free Academic Texts on Data Mining An Introduction to Statistical Learning with Applications in R: Covers […]