Titlebook: Beginning Data Science in R; Data Analysis, Visua Thomas Mailund Book 20171st edition Thomas Mailund 2017 R.programming.statistics.data sci

先鋒派

ELUC

Ignatius G. Mattingly,Alvin M. LibermanThis chapter and the next concern the mathematical modeling of data that is the essential core of data science. We can call this statistics, or we can call it machine learning. At its core, it is the same thing. It is all about extracting information out of data.

沉思的魚(yú)

Information Processing in The Nervous SystemThis chapter looks at R’s flavor of object oriented programming. Actually, R has three different systems for object oriented programming: S3, S4, and RC. We will only look at S3, which is the simplest and (I believe) the most widely used.

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逗留

騙子

myriad

Working with Large Datasets,The concept of Big Data refers to very large datasets, sets of sizes where you need data warehouses to store the data, where you typically need sophisticated algorithms to handle the data, and distributed computations to get anywhere with it. At the very least, we talk many gigabytes of data but also are often dealing with terabytes or exabytes.

留戀

Nefarious

Object Oriented Programming,This chapter looks at R’s flavor of object oriented programming. Actually, R has three different systems for object oriented programming: S3, S4, and RC. We will only look at S3, which is the simplest and (I believe) the most widely used.

Cloudburst

Building an R Package,You now know how to write functions and create classes in R, but neither functions nor classes is the unit you use for collecting and distributing R code. That unit is the package.