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

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103 MB
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14
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Added
05/13/19 at 7:50pm GMT+1
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2ad57fab031689429b90ca6d96d414487287e238

Description
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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Stream Course

File list
  • [TutorialPace.com] [DataCamp] Writing Efficient R Code - [TP]
  • 01_The art of benchmarking/01_Welcome.mp4 7.4 MB
  • 01_The art of benchmarking/02_Benchmarking.mp4 12.3 MB
  • 01_The art of benchmarking/03_How goood is your machine.mp4 7.6 MB
  • 02_Fine tuning efficient base R/04_Memory allocation.mp4 8.4 MB
  • 02_Fine tuning efficient base R/05_Importance of vectorizing your code.mp4 5.9 MB
  • 02_Fine tuning efficient base R/06_Data frames and matrices.mp4 7.1 MB
  • 03_Diagnosing problems code profiling/07_What is code profiling.mp4 11.4 MB
  • 03_Diagnosing problems code profiling/08_Profvis larger example.mp4 7.6 MB
  • 03_Diagnosing problems code profiling/09_Monopoly overview.mp4 4.3 MB
  • 04_Turbo charged code parallel programming/10_CPUs why do we have more than one.mp4 3.3 MB
  • 04_Turbo charged code parallel programming/11_What sort of programmings benefit from parallel computing.mp4 7 MB
  • 04_Turbo charged code parallel programming/12_The parallel package parApply.mp4 7.4 MB
  • 04_Turbo charged code parallel programming/13_The parallel package parSapply.mp4 11.8 MB
  • 04_Turbo charged code parallel programming/14_You can write efficient R code.mp4 1.1 MB

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