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Using R for Big Data with Spark

AuthorAuthor: art_links | DateDate: 12-07-2018, 08:06
Using R for Big Data with Spark

Using R for Big Data with Spark
HDRips | MP4/AVC, ~592 kb/s | 1280x720 | Duration: 02:20:02 | English: AAC, 128 kb/s (2 ch) | 731 MB
Genre: Development / Programming

Data analysts familiar with R will learn to leverage the power of Spark, distributed computing and cloud storage in this course that shows you how to use your R skills in a big data environment.

You'll learn to create Spark clusters on the Amazon Web Services (AWS) platform; perform cluster based data modeling using Gaussian generalized linear models, binomial generalized linear models, Naive Bayes, and K-means modeling; access data from S3 Spark DataFrames and other formats like CSV, Json, and HDFS; and do cluster based data manipulation operations with tools like SparkR and SparkSQL. By course end, you'll be capable of working with massive data sets not possible on a single computer. This hands-on class requires each learner to set-up their own extremely low-cost, easily terminated AWS account.

Discover how to use your R skills in a big data distributed cloud computing cluster environment
Gain hands-on experience setting up Spark clusters on Amazon's AWS cloud services platform
Understand how to control a cloud instance on AWS using SSH or PuTTY
Explore basic distributed modeling techniques like GLM, Naive Bayes, and K-means
Learn to do cloud based data manipulation and processing using SparkR and SparkSQL
Understand how to access data from the CSV, Json, HDFS, and S3 formats

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