Learn about the concept and significance of cloud computing and virtualization in data science.
- Cloud computing refers to the use…of a collection of remote servers,…connected via computer networks…and available through the internet.…Virtualization is what implements cloud computing.…It blurs the boundaries between physical computers…by allowing multiple logical machines to be created…on one hardware platform, like a server.…These two things in conjunction play such an important role…in making data science applications possible.…
Let's explore why.…A large number of organizations today…still use their local servers…but many of them have already migrated…to the cloud computing model due…to its more economically-efficient nature.…Why is cloud computing cheaper?…Well, that's partially due to economies of scale.…Basically, what that means is…that more volume leads to more savings.…You see, cloud computing companies specialize…in managing server farms.…
That means they're handling a lot of volume.…They're distributing their fixed costs over more services.…They have their know-how in maximizing their profit…while minimizing their expenses.…
- 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
Course organization1m 17s
1. Introduction to Data Science
2. Cloud Computing
3. Distributed File Systems
4. Distributed Processing
5. Machine Learning
6. Case Study
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