[TutorialPace.com] [DataCamp] Writing Efficient R Code - [TP]

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size102.6 MB
  • Uploaded ByTutorialPace
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  • Last checkedMay. 15th '19
  • Date uploadedMay. 14th '19
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The beauty of R is that it is built for performing data analysis. The downside is that sometimes R can be slow, thereby obstructing our analysis. For this reason, it is essential to become familiar with the main techniques for speeding up your analysis, so you can reduce computational time and get insights as quickly as possible.

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[TutorialPace.com] [DataCamp] Writing Efficient R Code - [TP] 04_Turbo charged code parallel programming
  • 14_You can write efficient R code.mp4 (1.1 MB)
  • 10_CPUs why do we have more than one.mp4 (3.3 MB)
  • 11_What sort of programmings benefit from parallel computing.mp4 (7.0 MB)
  • 12_The parallel package parApply.mp4 (7.4 MB)
  • 13_The parallel package parSapply.mp4 (11.8 MB)
03_Diagnosing problems code profiling
  • 09_Monopoly overview.mp4 (4.3 MB)
  • 08_Profvis larger example.mp4 (7.6 MB)
  • 07_What is code profiling.mp4 (11.4 MB)
02_Fine tuning efficient base R
  • 05_Importance of vectorizing your code.mp4 (5.9 MB)
  • 06_Data frames and matrices.mp4 (7.1 MB)
  • 04_Memory allocation.mp4 (8.4 MB)
01_The art of benchmarking
  • 01_Welcome.mp4 (7.4 MB)
  • 03_How goood is your machine.mp4 (7.6 MB)
  • 02_Benchmarking.mp4 (12.3 MB)

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