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Lynda - Scala Essential Training For Data Science
TORRENT SUMMARY
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Discover how to leverage Scala—the popular language that combines object-oriented design with functional programming—in your data science work. In this course, learn about the Scala features most useful to data scientists, including custom functions, parallel processing, and programming Spark with Scala. Dan Sullivan kicks off the course with an introduction for non-Scala programmers. Next, he describes how to use SQL from Scala—a particularly useful concept for data scientists, since they often have to extract data from relational databases. He then covers parallel processing constructs in Scala, sharing techniques that are useful for medium-sized data sets that can be analyzed on a single server with multiple cores.
Dan also focuses on using Scala with Spark, a distributed processing platform. He first describes how to work with Resilient Distributed Datasets (RDDs)—a fundamental Spark data structure—and then explains how to use Scala with Spark DataFrames, a new class of data structure specially designed for analytic processing. He wraps up the course by providing a summary of advantages of using Scala for data science.
Topics include:
The advantages of Scala for data science
Scala data types
Scala arrays, vectors, and ranges
Parallel processing in Scala
Mapping functions over parallel collections
When and when not to use parallel collections
Using SQL in Scala
Scala and Spark RDDs
Scala and Spark DataFrames
Creating DataFrames
Official Lynda Tutorial Link
VISITOR COMMENTS (0 )
FILE LIST
Filename
Size
00. Introduction/01. Welcome.mp4
3.6 MB
00. Introduction/02. What you should know.mp4
1.3 MB
00. Introduction/03. Using the exercise files.mp4
1007.5 KB
01. Introduction to Scala/01. The advantages of Scala for data science.mp4
4.7 MB
01. Introduction to Scala/02. Installing Scala.mp4
4.2 MB
01. Introduction to Scala/03. Scala data types.mp4
7.1 MB
01. Introduction to Scala/04. Scala collections.mp4
1.8 MB
01. Introduction to Scala/05. Scala sets Scala arrays, vectors, and ranges.mp4
8.9 MB
01. Introduction to Scala/06. Scala maps.mp4
6.3 MB
01. Introduction to Scala/07. Scala expressions.mp4
4.9 MB
01. Introduction to Scala/08. Scala functions.mp4
3.8 MB
01. Introduction to Scala/09. Scala objects.mp4
11.6 MB
02. Parallel Processing in Scala/01. Advantages of parallel collections.mp4
5.9 MB
02. Parallel Processing in Scala/02. Creating parallel collections.mp4
4.8 MB
02. Parallel Processing in Scala/03. Mapping functions over parallel collections.mp4
6.1 MB
02. Parallel Processing in Scala/04. Filtering parallel collections.mp4
7 MB
02. Parallel Processing in Scala/05. When and when not to use parallel collections.mp4
2.5 MB
03. Using SQL in Scala/01. Installing PostgreSQL.mp4
3.5 MB
03. Using SQL in Scala/02. Loading data into PostgreSQL.mp4
4 MB
03. Using SQL in Scala/03. Connecting to PostgreSQL.mp4
6.9 MB
03. Using SQL in Scala/04. Querying with SQL strings.mp4
5.4 MB
03. Using SQL in Scala/05. Querying with prepared statements.mp4
6.1 MB
03. Using SQL in Scala/06. Summary of SQL in Scala.mp4
1.2 MB
04. Scala and Sparks RDDs/01. Introduction to Spark.mp4
3 MB
04. Scala and Sparks RDDs/02. Installing Spark.mp4
4 MB
04. Scala and Sparks RDDs/03. Getting Started with Spark RDDs.mp4
7.9 MB
04. Scala and Sparks RDDs/04. Mapping Functions over RDDs.mp4
13.6 MB
04. Scala and Sparks RDDs/05. Statistics over RDDs.mp4
16 MB
04. Scala and Sparks RDDs/06. Summary of Scala and Spark RDDs.mp4
707.9 KB
05. Scala and Spark DataFrames/01. Creating DataFrames.mp4
9 MB
05. Scala and Spark DataFrames/02. Grouping and filtering on DataFrames.mp4
9.4 MB
05. Scala and Spark DataFrames/03. Joining DataFrames.mp4
5.8 MB
05. Scala and Spark DataFrames/04. Working with JSON files.mp4
4.2 MB
05. Scala and Spark DataFrames/05. Summary of Scala and Spark DataFrames.mp4
1 MB
06. Conclusion/01. Review of Scala for data science.mp4
