LAUNCHING THE OS ON THE TOP OF AWS CLOUD ,RUNNING THE DOCKER CONTAINER IN THE OS & DEPLOYING THE MACHINE LEARNING MODEL IN THE DOCKER CONTAINER

Terraform + Docker + AWS + Machine Learning

Technologies that I have used :-

𝑻𝒆𝒓𝒓𝒂𝒇𝒐𝒓𝒎

𝑨𝑾𝑺 𝑪𝒍𝒐𝒖𝒅

𝑴𝒂𝒄𝒉𝒊𝒏𝒆 𝑳𝒆𝒂𝒓𝒏𝒊𝒏𝒈

𝑫𝒐𝒄𝒌𝒆𝒓

𝙋𝙮𝙩𝙝𝙤𝙣

.

Terraform —

Terraform is an open-source infrastructure as code software tool created by HashiCorp. Users define and provide data center infrastructure using a declarative configuration language known as HashiCorp Configuration Language, or optionally JSON.

Amazon Web Services Cloud (AWS) —

Amazon Web Services is a subsidiary of Amazon providing on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.

Docker —

Docker is a set of platform as a service products that use OS-level virtualization to deliver software in packages called containers. Containers are isolated from one another and bundle their own software, libraries and configuration files; they can communicate with each other through well-defined channels.

Python —

Python is an interpreted high-level general-purpose programming language. Python’s design philosophy emphasizes code readability with its notable use of significant indentation.

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. … Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse.

Machine Learning —

Machine learning is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence.

Because of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It’s a science that’s not new — but one that has gained fresh momentum.

𝑷𝑹𝑶𝑱𝑬𝑪𝑻 𝑫𝑬𝑺𝑪𝑹𝑰𝑷𝑻𝑰𝑶𝑵 :-

I will be launching the instance(OS) on the top of AWS Cloud & will install docker in it to launch a container inside the OS.

𝙏𝙝𝙞𝙨 𝙬𝙝𝙤𝙡𝙚 𝙞𝙣𝙛𝙧𝙖𝙨𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚 𝙬𝙞𝙡𝙡 𝙗𝙚 𝙙𝙤𝙣𝙚 𝙗𝙮 𝙏𝙚𝙧𝙧𝙖𝙛𝙤𝙧𝙢.

After the container has been launched , I’ll install the required python libraries for to create my machine learning model in the container.

𝗣𝘆𝘁𝗵𝗼𝗻 𝗹𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗱 𝗳𝗼𝗿 𝗺𝘆 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹 𝗮𝗿𝗲 :
- 𝗡𝘂𝗺𝗽𝘆
- 𝗣𝗮𝗻𝗱𝗮𝘀
- 𝗦𝗸𝗹𝗲𝗮𝗿𝗻
- 𝗝𝗼𝗯𝗹𝗶𝗯

I have my machine learning code in the Github.

I will also install git package in docker container to clone my code from github.

Then I’ll send my code to the container so that I can execute the machine learning code inside it.

That’s solved , my whole infrastructure is ready with end to end automated.

THANKS FOR READING :-)