Learn about how Weka can run on Spark.
- Although, running WEKA in its stand-alone mode is…perfectly fine for many of our daily data-sized tests,…we do need to tap into the power of distributed processing…from time to time, especially when our dataset falls…in the realm of big data.…Since we already have well-known tools like Spark…available for distributed processing tests,…it would be ideal if WEKA can leverage the technology…and WEKA does provide a way to harness…the power of Spark. Let's see how we can go about…configuring WEKA to take advantage of Spark.…
From the gui chooser, go to tools…and select package manager.…In the package search window, type Spark and press enter.…Choose distributed WEKA Spark.…Click install and click yes.…Click okay.…Click yes.…
Once you install the Spark package, we need to restart WEKA.…Close the package manager, close WEKA gui chooser.…Let's restart WEKA.…Click okay.…To allow you to run a distributed WEKA job…in a user-friendly way, WEKA provides an option…called KnowledgeFLow.…Click on KnowledgeFlow, and the WEKA KnowledgeFlow…
Author
Jungwoo Ryoo
Released
8/30/2018- Enabling technologies in data science
- Cloud computing and virtualization
- Installing and working with Proxmox, Hadoop, Spark, and Weka
- Managing virtual machines on Proxmox
- Distributed processing with Spark
- Fundamental applications of machine learning
- Distributed systems and distributed processing
- How Hadoop, Spark, and Weka can work together
Skill Level Beginner
Duration
Views
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Introduction
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Course organization1m 17s
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1. Introduction to Data Science
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Introduction1m 51s
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Data science2m 53s
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Fundamental skills3m 42s
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Enabling technologies2m 4s
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2. Cloud Computing
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Cloud fundamentals3m 29s
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Types of cloud3m 19s
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Solution providers2m 22s
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Proxmox: Installation2m 26s
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3. Distributed File Systems
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Distributed file systems2m 44s
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Fundamentals2m 45s
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Hadoop hands-on2m 8s
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Hadoop: Preparation4m 11s
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Hadoop: Installation4m 18s
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Hadoop: MapReduce hands-on8m 52s
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4. Distributed Processing
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Spark: Installation6m 24s
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Spark: Spark shell4m 28s
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Spark: pyspark4m 32s
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Spark: Application4m 1s
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5. Machine Learning
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Machine learning2m 41s
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Fundamentals2m 16s
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Types of machine learning2m 59s
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Weka: Installation2m 33s
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Weka: GUI3m 35s
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Weka: Training vs. testing3m 21s
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Weka: Clustering2m 12s
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6. Case Study
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Putting it all together2m 42s
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Hadoop cluster: Operation4m 57s
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Spark, YARN, and Hadoop6m 42s
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Weka and Spark3m 12s
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Conclusion
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Next steps41s
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Video: Weka and Spark