پیشنهاد فرادرس

آموزش برنامه نویسی پیشرفته SAS برای کاربران R – قسمت 2

دسته بندی ها: کلان داده (Big Data) ، آموزش R ، آموزش های لیندا (Lynda) ، پایگاه داده

برنامه نویسی پیشرفته SAS برای کاربران R به دنبال تکنیک های پیچیده و مفاهیمی است که می تواند به شما در درک R-زبان داده های بزرگ در محیط SAS در سطح پیشرفته کمک کند. در این دوره با چندین مفاهیم برنامه نویسی پیشرفته SAS، اصول اولیه زبان ماتریس تعاملی (IML)، تولید عدد تصادفی در IML، ماژول های IML معمولی و نحوه کشیدن یک مجموعه داده SAS به یک ماتریس IML و نحوه فراخوانی با R از SAS آشنا می شوید.

سرفصل:

  • زبان ماتریس تعاملی (IML)
  • شباهت ها به R
  • کار در حالت تعاملی در SAS Studio
  • تولید عدد تصادفی در IML
  • ایجاد ماژول ها
  • فراخوانی با R از SAS
  • ایجاد یا ویرایش یک مجموعه داده SAS با یک ماتریس IML
  • حرکت کد، داده ها و نتایج بین SAS و R
Advanced SAS Programming for R Users, Part 2 Publisher:Lynda Author:Jordan Bakerman Duration:1h 37m Level:Advanced

Learn how to apply your understanding of R—the language of big data—in the SAS environment at an advanced level.
Released: 3/22/2018
Advanced SAS Programming for R Users explores sophisticated techniques and concepts that can help you apply your understanding of R—the language of big data—in the SAS environment at an advanced level. In this course, Jordan Bakerman walks through several advanced SAS programming concepts. To begin, he covers the basics of the Interactive Matrix Language (IML), and discusses random number generation in IML, common IML modules, and how to pull a SAS dataset into an IML matrix. He then discusses how to call R from SAS, work with R from IML, and more. To get the most from this course, make sure to watch Advanced SAS Programming for R Users, Part 1.
Note: You can visit the SAS site to obtain a copy of the software, and use the company's online data sets to do the course exercises.
Topics include:
Interactive Matrix Language (IML)
Similarities to R
Working in Interactive mode in SAS Studio
Random number generation in IML
Creating modules
Calling R from SAS
Creating or editing a SAS dataset with an IML matrix
Moving code, data, and results between SAS and R
Introduction
Welcome
1m 4s
1. Interactive Matrix Language (IML)
The basics of IML
3m 21s
Similarities to R
2m 37s
Additional techniques
2m 17s
Demo: Working in Interactive mode in SAS Studio
2m 12s
Demo: Basic matrix operations by example
6m 10s
Modules: Functions and subroutines
3m 12s
Random number generation in IML
2m 47s
Demo: Simple linear regression from scratch
6m 19s
Common IML modules
5m 12s
Demo: Navigating the SAS/IML documentation
1m 51s
Creating modules
4m 57s
Storage techniques
3m 24s
Demo: Creating functions and subroutines
4m 19s
Pulling a SAS dataset into an IML matrix
2m 39s
Creating or editing a SAS dataset with an IML matrix
3m 4s
Demo: Calling SAS datasets from IML
4m 3s
Calling SAS procedures from IML
3m 1s
Demo: Submitting SAS procedures
2m 11s
Syntax for simulations
4m 5s
Demo: The Monty Hall simulation
4m 19s
Simulation techniques in general
2m 44s
Demo: Sampling distribution method 1, entirely in IML
2m 22s
Demo: Sampling distribution method 2, iteratively calling SAS procedures from IML
2m 56s
Demo: Sampling distribution method 3, intelligently calling SAS procedures with the BY statement
5m 14s
2. A Bridge between SAS and R
Calling R from SAS in general
1m 53s
Readying your machine to call R
1m 30s
Moving code, data, and results between SAS and R
2m 49s
Demo: Working with R from IML
5m 15s

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