Join Jungwoo Ryoo for an in-depth discussion in this video Course organization, part of Data Science Tools of the Trade: First Steps.
- [Instructor] When it comes to learning, doing is always better than watching. I had this in mind when I designed this course. You should be able to follow along with my demos for the most part. However, the Hadoop cluster installation piece is quite complicated, so you will not be able to follow here. It takes a lot of time to go through all the details, and I am showing you only the highlights of the installation process. But you'll still have a good feel for how everything gets installed, configured and used.
If you're really interested, you can install your own Hadoop cluster using the tutorials available through the apache.org documentations. One more thing I'd like to mention is that there may be some discrepancies between what I show you here and what you get when you install your Proxmox software. This is because I had to install some extra VMs for preparation and testing purposes before I started my demonstrations.
None of these differences will affect learning. Now, with this in mind, let's get started on this journey.
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: Course organization