Cloud Computing - An Overview

December 23, 2021

Cloud computing is revolutionizing how businesses meet their IT needs. Cloud computing offers scalability, high performance, cost savings, and economies of scale while offering global reach without sacrificing control or security. The idea behind cloud computing seemed too unbelievable to be true - that you would access your computer's operating system over the Internet?! Today the cloud is no longer science fiction; this very concept has revolutionized business by enabling people to work anywhere at any time.

What is Cloud Computing?

Cloud computing is a delivery system that provides access to a whole industry of resources to store and process data, including software applications. From a business perspective, this service entirely gets rid of the task of having to purchase and maintain physical infrastructure. This is as everything is done online — making it more flexible for companies, as they don't need to hire additional staff or account for large purchases, such as server racks and processors. However, they can give 100% focus on hiring specific individuals for special roles within the said company (e.g. developers).

Cloud Deployments Come in a Variety of Types

Deployment models are important because they help us determine what type of access your cloud has.

Public Cloud: With the public cloud, systems and services can be easily accessible to the public. While this may seem like a benefit, the public cloud is often less secure than other types of hosting because you're putting all your data right there for anyone with an Internet connection to potentially access.

Private Cloud: A private cloud allows for private networks that are maintained within an organization. This type of network is popular because it's not open to the public.

Hybrid Cloud: This cloud is an effective blend of public and private resources, with each providing its specialties. In this cloud, vital tasks are handled by the private cloud, and the public cloud handles non-critical tasks.

Multi-Cloud: Multi-cloud is the one where a business would be able to access different public clouds from multiple vendors, instead of just one. This way, the company would have the ability to utilize various storage and computing resources from different providers, eliminating any redundancy issues that come from being dependent on one provider.

Benefits of Cloud Computing

The benefits of cloud computing are numerous:

  • Over the Internet, one may access apps as utilities.
  • The applications can be manipulated and configured online at any moment.
  • To access or operate cloud applications, you do not need to install any software.
  • Cloud resources can be accessed across the network in a way that allows any sort of client to access them regardless of platform.
  • Cloud computing allows the usage of services and resources on demand. This means that without interacting with the cloud service provider, the resources can still be utilized.

Various Cloud Terminologies

Private Cloud: Private clouds are like having your own dedicated cloud computer. Instead of relying on shared resources hosted on the provider's data center, bare metal users benefit from their own resources and can be freely scaled as needed. Bare metal is a good option for entrepreneurial and large enterprises that want to deploy their applications without any downtime.

VM: A VM is a digital copy of a computer that works alongside other virtual computers to complete specific tasks. While a computer can operate on its own, a virtual can take part in complex systems coordinated by another component called the hypervisor. Using the same software from a single computer, a hypervisor creates an environment where many VMs can share different parts of a machine's hardware.

API: A Cloud API is your on-demand app developer. It is a powerful tool for cloud computing services, and it allows one computer program to make its data and functionality available for other programs to use or tap into. This means that instead of reinventing the wheel for every new project you undertake, you can simply use programming tools already online via APIs to connect software components across your network.

Open Source: An open-source cloud is any public, private, or hybrid cloud, that is based entirely on open source technologies and software. This most often applies to internet-based data centers whose functionality may be offered via SaaS, IaaS, and PaaS models.

Traditional IT Infrastructure

Traditional IT infrastructure refers to the use of physical servers for storing digital assets and running complete networking systems involved in daily operations. In this type of computing, the only means through which users can access their data is by logging in from a single device or through an authorized network. In traditional computing, users have no freedom to use their data anywhere they choose.

Limitations of Traditional IT Infrastructure

  • It deals with the deployment of various services on a local server.
  • Users can only access data on the system where it is kept.
  • Data and information can be accessed without the use of an internet connection.
  • Cloud computing is more accessible than traditional computing since data can be accessed from any location if a user wants to access it from another device.
  • It doesn't have any sustainability or flexibility.
  • When compared to cloud computing, it offers less storage.

Conclusion

There are many different factors to consider when it comes to choosing between cloud computing. The cloud has many benefits, but it also has its downsides. The decision to choose cloud computing must be made by each individual business based on its unique needs. This post will hopefully give you some information that will help you decide.

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The problem with customer acquisition

As an organization, when working in a diverse and competitive market like India, you need to have a well-defined customer acquisition strategy to attain success. However, this is where most startups struggle. Now, you may have a great product or service, but if you are not in the right place targeting the right demographic, you are not likely to get the results you want.

To resolve this, typically, companies invest, but if that is not channelized properly, it will be futile.

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Reference Links

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State-of-the-art Technology Used by the Datasets for the Reconstruction of 3D Objects

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The testing will also be done on the same parameters, which will also help to create a uniform, cluttered background, or both.

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  • Network architecture used

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  • Training used

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Volumetric representations and surface representations can do the reconstruction. Powerful computer systems need to be used for reconstruction.

Given below are some of the places where 3D Object Reconstruction Deep Learning Systems are used:

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  • They can be used in plastic surgery where the organs, face, limbs or any other portion of the body has been damaged and needs to be rebuilt.
  • It can be used in airport security, where concealed shapes can be used for guessing whether a person is armed or is carrying explosives or not.
  • It can also help in completing DNA sequences.

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Reference Links

https://tongtianta.site/paper/68922

https://github.com/natowi/3D-Reconstruction-with-Deep-Learning-Methods

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What is Deep Q-Learning?

Deep Q-Learning utilizes the principles of Q-learning, but instead of using the Q-table, it uses the neural network. The algorithm of deep Q-Learning uses the states as input and the optimal Q-value of every action possible as the output. The agent gathers and stores all the previous experiences in the memory of the trained tuple in the following order:

State> Next state> Action> Reward

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What is Reinforcement Learning?

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Now, the understanding of reinforcement learning is incomplete without knowing about Markov Decision Process (MDP). MDP is involved with each state that has been presented in the results of the environment, derived from the state previously there. The information which composes both states is gathered and transferred to the decision process. The task of the chosen agent is to maximize the awards. The MDP optimizes the actions and helps construct the optimal policy.

For developing the MDP, you need to follow the Q-Learning Algorithm, which is an extremely important part of data science and machine learning.

What is Q-Learning Algorithm?

The process of Q-Learning is important for understanding the data from scratch. It involves defining the parameters, choosing the actions from the current state and also choosing the actions from the previous state and then developing a Q-table for maximizing the results or output rewards.

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Reference Links

https://analyticsindiamag.com/comprehensive-guide-to-deep-q-learning-for-data-science-enthusiasts/

https://medium.com/@jereminuerofficial/a-comprehensive-guide-to-deep-q-learning-8aeed632f52f

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