AWS for Machine Learning — Part 2
A detailed explanation of creating an AWS account and using AWS services for free
📄Contents.
1. Cloud Computing.
2. What is AWS?
3. AWS for machine learning
2.1 Definition of AWS
As Amazon explains in their documentation.
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.
2.2. Fields using AWS.
Any application which would require computing can be moved to the cloud. Some of the examples include Manufacturing, Media, Enterprises, etc.
2.2 Services Offered
Amazon Web Services offers a broad set of global cloud-based products including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security, and enterprise applications.
The Top 10 Most Used AWS Services are:
1. Amazon EC2: Amazon Elastic Compute Cloud — This service lets you create your own virtual machines on which multiple services or programming languages or scripts can be run.
2. Amazon RDS: Amazon Relational Database Service — This service creates dedicated instances of databases within minutes. Not to mention, these instances can support multiple database engines including SQL Server, SQL, PostgreSQL, and more.
3. Amazon Simple Storage Service (S3) — This is a storage service that helps store data on cloud buckets.
4. Amazon CloudFront — This service helps to improve website speed and access to cloud-based data.
5. Amazon VPC — This service creates a private virtual network that cannot be accessed by anyone or anything except the people and systems you authorize.
6. Amazon SNS — This is an event-driven computing hub that alerts subscriber services to perform tasks automatically in response to specified triggers. This service allows sending notifications to any users on any platform
7. AWS Beanstalk — It was created to help developers manage website infrastructure.
8. AWS Lambda — Provides with 1 million free requests. An example is sending a notification to the users using an app.
9. AWS Autoscaling — This service can manage fleets of servers and incoming traffic. Multiple instances are created when needed.
10. AWS IAM: Identity and Access Management (IAM) — This service offers an effective fortification of sensitive data and AWS resources. It’s just an additional layer of security that never hurts.
2.3 AWS services specific for Machine Learning.
Some of the services used by Data Scientists/Machine Learning Engineers are as follows.
- Amazon SageMaker — Build, train, and deploy machine learning models fast
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy ML models at scale. It removes the complexity from each step of the ML workflow so you can more easily deploy your ML use cases, anything from predictive maintenance to computer vision to predicting customer behaviors.
2.4 Creating an AWS account:
AWS account can be created and used for free for a year. Click on the link and then click on create a new AWS account and complete the signup process using your Gmail, personal details, and debit/credit card details.
If you have a question like I had — Why do I need to add a payment method if my account is covered by the AWS Free Tier?
2 rupees will be charged and send it back after two days to verify the user.
AWS always throws a notification stating that you will be charged if you use the service exceeding the free tire limit.
I don't think for learning you would need any paid services.
So now you have created a free AWS account next article I will be showing how to implement a Machine Learning project on AWS.
Want to learn more check out the topics below.
More references:
- Artificial Intelligence real or is it just a hype of this decade??
- Artificial Intelligence: Definition, Types, Examples, Technologies
- Artificial Intelligence vs Machine Learning
- Why Machine learning for achieving Artificial Intelligence? “ The Need for Machine Learning”
- Machine Learning Types and Algorithms
- Linear Regression Part -1
- Linear Regression Part -2(example implementation)
- How to get AI related jobs?
- So you want to build a chatbot from scratch?
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