Building Practical Recommendation Engines – Part 2

Building Practical Recommendation Engines – Part 2

Free Download Udemy Building Practical Recommendation Engines – Part 2. With the help of this course, you can Use behavioral and historical data to predict the future.

This course was created by Packt Publishing for a duration of 02:12:15 explained in English. There are a lot of users enrolled in this course, so don’t wait to download yours now.

Before you enroll this course you need to have To work along this course you'll need to have a basic understanding of recommendation engines using R. Familiarity with Python, Spark, Neo4j and Hadoop would be beneficial.The software requirements of the course are:Anaconda 4.2 for Python 3.5Neo4j 3.0.6Spark 2.0Hadoop 2.5 -Mahout 0.12Java 7/Java 8WINDOWS 7+/Centos 6.

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