Delve into serverless computing, develop AWS Lambda Functions, and deploy an end-to-end machine learning pipeline. Gain insights into efficiently managing ML applications without infrastructure concerns.

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AWS_ACCESS_KEY_ID

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aws_serverless

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aws_serverless3

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Serverless computing makes the life of a developer easy by eliminating the pains of managing servers. You only need to write code—the serverless cloud services, such as AWS Lambda Functions, take care of infrastructure on their own. The Serverless framework provides easy to use commands and dashboards to make it even easier to use cloud services.

In this course, you’ll learn what serverless computing is and how the Serverless framework works. You’ll then get hands-on experience developing and deploying an AWS Lambda Function. Next, you’ll learn how to provide additional libraries using Layers in AWS Lambda. Having covered the basics, you’ll then deploy an end-to-end machine learning pipeline to the AWS cloud with a serverless approach.

Mastery over the serverless framework will give you the ability to focus on your machine learning problem and pipeline, instead of worrying about infrastructure management. This will help you get your machine learning applications to market faster and scale them seamlessly!

Mastering Serverless Computing for Data Science

**(True or False)** When dealing with irregular and sporadic prediction requests, we should prefer AWS Lambda over a VM.

(True or False) When dealing with irregular and sporadic prediction requests, we should prefer AWS Lambda over a VM.

You can deploy any custom runtime of your choice on AWS Lambda.

You can deploy any custom runtime of your choice on AWS Lambda.

What are AWS Lambda's maximum memory and timeout quotas?

What are AWS Lambda’s maximum memory and timeout quotas?

It would _exclude_ all files by default with individual exceptions.

It would _include_ all files by default with individual exceptions.

It would _exclude_ everything, except the stuff you explicitly indicate to keep.

What effect would the following statement from the `serverless.yml` file have on your deployment?

**package:**

    individually: true
    patterns:
	       - “!.**/”

What effect would the following statement from the <code>serverless.yml</code> file have on your deployment?
package:
<pre><code>individually: true
patterns:
 - “!.**/”</code></pre>

It organizes the python requirements for our Lambda function.

It helps with organizing, building and packaging Python requirements for our Lambda functions.

It organizes and builds the python requirements for our Lambda function.

What benefit do we get from using the `serverless-python-requirements` plugin for our use-case?

What benefit do we get from using the <code>serverless-python-requirements</code> plugin for our use-case?

Test your knowledge of the ML model in AWS Lambda.

Basics of Serverless Computing

ML Model Dockers in AWS Lambda

Serverless Architecture for Data Science

Conclusion

Appendix

Quiz: ML Model in AWS Lambda