AWS Machine Learning / AI

Paths

AWS Machine Learning / AI

Authors: Mike Erickson, Mark Nunnikhoven, Raluca Bolovan, Fernando Medina Corey, Tom Compagno, Alan Jones, Jorge Vasquez, David Tucker

AWS has a number of machine learning and artificial intelligence services and products that can be used in conjunction with each other to make smart applications. In this path... Read more

What you will learn:

  • Amazon Lex
  • Amazon Comprehend
  • AWS Polly
  • Amazon Translate
  • Amazon Transcribe
  • AWS Rekognition
  • Sagemaker
  • Deep Learning on AWS

Pre-requisites

This path is for learners who possess a general knowledge of cloud computing and application development. They do not need to be experts in AI or Machine learning but will learn how to use the plug and play options on AWS in their applications.

Beginner

In this section you will learn about your first artificial intelligence service that you can use in your application, Amazon Lex.

Getting Started with Amazon Lex

by Mike Erickson

Mar 13, 2018 / 1h 57m

1h 57m

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Description

The creation of an interactive and intelligent application is helped by the use of automatic speech recognition (ASR) and natural language understanding (NLU). In Getting Started with Amazon Lex, you will be introduced to the skills required to leverage Amazon Lex to build these user interactions for the applications you create. First, you will learn how to define the intents that the ChatBot will fulfill for the user. Next, you will explore how to create the slots that will gather the required information from your user. Finally, you will discover how to implement Lambda functions that process the information gathered by your ChatBot to complete the desire of your users. When you are finished with this course, you will be prepared to create simple informational bots using Amazon Lex.

Table of contents
  1. Course Overview
  2. Introducing Lex, Amazon Lex
  3. Building Your First Amazon Lex Chatbot
  4. Improving Your Prompts
  5. Adding Fulfillment
  6. Managing Your Chatbot Lifecycle
  7. Adding Error Handling

Intermediate

In this section you will learn about the bulk of the options for AI on AWS for developers. Each individual course covers a machine learning or artificial intelligence service.

Analyzing Text on AWS with Amazon Comprehend

by Mark Nunnikhoven

Jun 28, 2019 / 1h 56m

1h 56m

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Description

At the core of text analysis in the AWS Cloud is a thorough knowledge of Amazon Comprehend. In this course, Analyzing Text on AWS with Amazon Comprehend, you’ll learn how to use the service to extract insights and deep analysis about a given text. First, you’ll discover how the service is structured and common usage patterns for all of its features. Next, you’ll explore more advanced analysis concepts using an asynchronous request pattern. Finally, you’ll see how easy it can be to conduct complex topic modeling analysis. When you’re finished with this course, you’ll have a foundational knowledge of how to use Amazon Comprehend to analyze and understand any document set that will help you as you move forward and understand how to apply machine learning to real world problems.

Table of contents
  1. Course Overview
  2. Introducing Amazon Comprehend & Natural Language Processing
  3. The Basic Building Blocks of Analysis
  4. Advanced Text Analysis
  5. Discovering Document Topics
  6. Security & Privacy Concerns

Building a Voice-enabled Serverless Website with AWS Polly

by Raluca Bolovan

Jul 10, 2018 / 1h 46m

1h 46m

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Description

With the abundance of information available, it’s becoming exponentially harder to keep your users’ focus on the content you have relentlessly created. With the emergence of AWS Polly, you can breathe life into your ideas, by choosing the most evocative voice to convey your message. In this course, Building a Voice-enabled Serverless Website with AWS Polly, you’ll go through the journey of designing, building, and automating your content website, with the result of enriching your users’ experience. First, you'll explore what makes AWS Polly special and why it is the right choice for building a close interaction with your audience. Next, you'll experience the iterative process of coming up with an architecture for your website that resonates with the intent to serve your users. You'll start with the fundamentals of setting up the infrastructure for the website, ranging from local development to seeing and hearing your creation deployed on the Web. By combining concepts like Serverless computing, Infrastructure as code, CI/CD, you'll see how these new trends can be used together to save you time and make your applications resilient. Then, you'll iteratively improve the way the speech gets generated, with the help of AWS Lambda. Finally, you'll unearth new possibilities of extending and creating other voice-enabled architectures for captivating your audience. When you're finished with this course, you'll have a clear understanding of how you can use Polly to automatically narrate your content, your own functional serverless website that you can customize, and a good foundation to confidently create other applications using emerging tech methodologies.

Table of contents
  1. Course Overview
  2. Getting Started with AWS Polly
  3. Architecting and Setting Up a Speaking Website with Polly and Hugo
  4. Enhancing Your Website's Voice Capabilities
  5. Reflecting On and Extending Polly's Role in Your Site

Translating Languages on AWS with Amazon Translate

by Fernando Medina Corey

Mar 8, 2019 / 2h 32m

2h 32m

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Description

Translating text at scale is a challenge for many organizations that want to make themselves understood internationally. In this course, Translating Languages on AWS with Amazon Translate, you will gain the ability to leverage Amazon Translate and neural machine translation in your applications. First, you will learn the basic context and benefits of neural machine translation tools. Next, you will discover how to leverage Amazon Translate APIs to scale your translation capabilities. Finally, you will explore how to integrate Amazon Translate with other AWS services such as Amazon Polly and Amazon CloudWatch. When you’re finished with this course, you will have the skills and knowledge of Amazon Translate needed to develop, secure, and monitor your own Amazon Translation applications and remove the restriction of language barriers.

Table of contents
  1. Course Overview
  2. Getting Started with Amazon Translate
  3. Translating Text in Different Formats
  4. Monitoring and Securing Amazon Translate
  5. Integrating Amazon Translate

Turning Speech into Text on AWS with Amazon Transcribe

by Tom Compagno

Aug 23, 2019 / 1h 29m

1h 29m

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Description

Digital recorded audio is a useful storage medium, but quickly becomes useless when it needs to be consumed quickly. In this course, Turning Speech into Text on AWS with Amazon Transcribe, you’ll gain the ability to leverage and scale the AWS Transcribe service to convert your recorded speech into flat text data. First, you’ll explore manual runs of transcription jobs. Next, you’ll discover how to scale up the process for higher impact transcriptions across your organization. Finally, you’ll learn how to combine transcription with AWS Translate to add even more flexibility for your global needs. When you’re finished with this course, you’ll have the skills and knowledge to alleviate the need to have people manually listen to and transcribe or translate recorded speech.

Table of contents
  1. Course Overview
  2. Creating and Running Transcription Jobs
  3. Monitoring and Managing Transcribe
  4. Integrating Transcribe

Advanced

In this section you will finish up with one last AI tool, Rekognition, and you'll also learn about the deeper side of machine learning with the powerful Sagemaker and Deep Learning Instances on AWS.

Developing Applications with AWS Rekognition

by Alan Jones

Sep 7, 2018 / 1h 27m

1h 27m

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Description

AWS Rekognition provides powerful services for image and video processing. This course, Developing Applications with AWS Rekognition, will demonstrate how these features can be applied to your applications. First, you will cover topics like biometric access based on facial recognition and detection of unsafe content. Next, you will learn how to implement person tracking in security videos and metadata discovery for social media applications. Finally, you will see how other AWS services, like EC2 and Lambda, can work together with Rekognition to build complete applications. When you're finished with this course, you will be ready to use all of the features of Rekognition for image and video processing.

Table of contents
  1. Course Overview
  2. Introduction to Rekognition
  3. Using the Image Features of Rekognition
  4. Using the Video Features of Rekognition
  5. Building a Complete Rekognition Application
  6. Conclusion

Build, Train, and Deploy Machine Learning Models with AWS SageMaker

by Jorge Vasquez

Jul 22, 2019 / 2h 41m

2h 41m

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Description

A fully managed machine learning service is a great place to start if you want to quickly get machine learning into your applications. In this course, Build, Train, and Deploy Machine Learning Models with AWS SageMaker, you will gain the ability to create machine learning models in AWS SageMaker and to integrate them into your applications. First, you’ll learn the basics and how to set up SageMaker. Next, you’ll discover how to build, train, and deploy models applied to Image Classification for breast cancer detection and how to integrate them into a REST API. Finally, you will even discover how to manage security and scalability in AWS SageMaker. When you’re finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

Table of contents
  1. Course Overview
  2. Getting Started with AWS SageMaker
  3. Building Machine Learning Models Using AWS SageMaker
  4. Training Machine Learning Models Using AWS SageMaker
  5. Deploying Machine Learning Models Using AWS SageMaker
  6. Managing Security and Scalability in AWS SageMaker

Deep Learning Instances and Frameworks on AWS

by David Tucker

Jul 17, 2019 / 1h 23m

1h 23m

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Description

Deep learning enables a new level of data analysis, but configuring custom compute resources to gain these insights can be extremely difficult. In this course, Deep Learning Instances and Frameworks on AWS, you will gain the ability to launch deep learning instances on EC2 and ECS. First, you will learn the types of Deep Learning AMIs provided by AWS. Next, you will analyze how to leverage popular deep learning frameworks on these instances. Finally, you will review how to manage and scale your deep learning activities on these instances. When you are finished with this course, you will be able to launch and utilize custom deep learning instances and leverage popular deep learning frameworks.

Table of contents
  1. Course Overview
  2. Introduction to Deep Learning AMIs
  3. Leveraging Deep Learning AMIs
  4. Managing Deep Learning Instances
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