What is Cloud Computing in Machine Learning?

How quickly things change when you are in the age of machine learning and artificial intelligence. We have seen Cloud computing evolving from a risky and confusing system to a very important strategy that organizations, doesn’t matter large and small are beginning to adopt these systems as a part of their IT strategy. Businesses are now starting to wonder not if they should be thinking about cloud computing, but what kinds of cloud computing models are best suited to solve their business problems.

Today, the type of cloud deployment system you should consider depends on your particular performance of your machine learning models, security requirements, and your specific business goals. In this article, I will give you complete knowledge of Cloud Computing for Machine Learning. At the end of this article, you will learn why machine learning practitioners need to know what is cloud computing and why we need it.

Also, Read – Stemming in Machine Learning.

What is Cloud Computing?

Cloud computing is a method of providing a set of shared computing resources that includes machine learning applications, computing, storage, networking, development and deployment platforms, and business processes. It transforms traditional siled IT assets into shared resource pools based on an underlying Internet foundation.

Clouds are available in different versions, depending on your needs. There are two main models of cloud deployment: public and private. Most of the organizations use the combination of private computing for data storage and public services as a hybrid environment.

The cloud does not exist independently of other business IT investments. The reality is that most businesses use a combination of public and private cloud services in conjunction with their data centre. Companies use different methods, depending on their business needs, to link and integrate these services. How you build your hybrid IT environment is determined by the complexity of the workloads and how you want to optimize the performance of those workloads to support your constituents.

Types of Cloud Computing Models

To understand the fundamentals of cloud computing requires understanding three main cloud delivery models:

IaaS

The provision of services such as hardware, software, storage, networking, data centre space and various utility software items on request. There are public and private versions of IaaS.

  • In public IaaS, the user needs a simple registration mechanism to acquire resources. When users feel like they no longer need the resources, they can simply de-provision them.
  • In a private IaaS, the IT organization or an integrator creates an infrastructure designed to deliver resources on-demand to internal users and sometimes to partners. IaaS is the foundational building block used by other cloud models. Some customers bring their own tools and software to build applications.

PaaS

A mechanism for combining IaaS with an abstract set of middleware, software development, and deployment tools that provide the organization with a consistent way to build and deploy applications in a cloud environment or on-site.

A PaaS environment supports coordination between the developer and the organization of operations, commonly referred to as DevOps. A PaaS offers a cohesive set of programming and middleware services that provide developers with a well-tested and well-integrated way to build applications in a cloud environment. A PaaS requires an infrastructure service

SaaS

A business application created and hosted by a supplier in a mutualized (shared) model. The SaaS application sits on top of a basic PaaS and IaaS. In fact, the SaaS environment can also be built directly on the IaaS platform. Typic, these underlying services are not visible to end-users of a SaaS application.

IaaS and PaaS are core services on which other cloud services will rely. IaaS itself is the foundation on which PaaS can be used to create value. It provides the infrastructure that developers can use to build applications.

For example, many organizations use IaaS and PaaS tied together for the development and operations process. These organizations can even use IaaS and PaaS to create true SaaS services. So in some ways, IaaS is the base of a pyramid with infrastructure at the bottom, middleware (PaaS) at the centre, and applications at the top.

Also, Read – Visualize a Decision Tree in Machine Learning.

I hope you liked this article on the use of cloud computing in Machine Learning. Feel free to ask your valuable questions in the comments section below. You can also follow me on Medium to learn every topic of Machine Learning.

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Aman Kharwal

I am a programmer from India, and I am here to guide you with Data Science, Machine Learning, Python, and C++ for free. I hope you will learn a lot in your journey towards Coding, Machine Learning and Artificial Intelligence with me.

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