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Rogerio Guimaraes

In this one-hour project, you will understand how Amazon Rekognition works for video analysis and what information is generated for video indexing. You will learn how to deploy a Web Application that uses the AWS SDK to upload and index videos to detect faces, objects, and labels in scenes, maturity content, identify celebrities, and more.

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In this one-hour project, you will understand how Amazon Rekognition works for video analysis and what information is generated for video indexing. You will learn how to deploy a Web Application that uses the AWS SDK to upload and index videos to detect faces, objects, and labels in scenes, maturity content, identify celebrities, and more.

Amazon Rekognition is one of the most used Artificial Intelligence services in AWS and is favored to analyze images and videos with colossal confidence and low costs.

Once you're done with this project, you will be able to use Amazon Rekognition to analyze and index your videos in just a few steps.

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What's inside

Syllabus

Project Overview
In this one-hour project, you will understand how Amazon Rekognition works for video analysis and what information is generated for video indexing. You will learn how to deploy a Web Application that uses the AWS SDK to upload and index videos to detect faces, objects, and labels in scenes, maturity content, identify celebrities, and more. Amazon Rekognition is one of the most used Artificial Intelligence services in AWS and is favored to analyze images and videos with colossal confidence and low costs. Once you're done with this project, you will be able to use Amazon Rekognition to analyze and index your videos in just a few steps.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills and knowledge in using Amazon Rekognition to analyze videos for faces, objects, labels, celebrities, and maturity content
Taught by Rogerio Guimaraes, an experienced instructor, whose work involves Amazon Rekognition
Explores Amazon Rekognition, a highly-used AI service for image and video analysis, that is favored by both industry and academia
Teaches skills highly relevant for professional use cases involving video analysis and indexing
Provides hands-on practice through a web application that uses the AWS SDK for video analysis and indexing, ensuring practical application of skills

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Deploy a Video indexing Application using Amazon Rekognition with these activities:
Review your knowledge of computer vision
Enhance your understanding of computer vision, which is the foundation for Amazon Rekognition, by reviewing your knowledge of its concepts and algorithms.
Browse courses on Computer Vision
Show steps
  • Read articles and blog posts on computer vision
  • Watch videos on computer vision
  • Complete a project related to computer vision
Review your knowledge of Python
Strengthen your foundation for this course by reviewing your knowledge of Python, which is used to develop the web application in this course.
Browse courses on Python
Show steps
  • Review your notes from a previous Python course
  • Take a practice quiz on Python
  • Complete a coding challenge in Python
Practice uploading and indexing videos
Reinforce your understanding of video indexing by practicing uploading and indexing videos using Amazon Rekognition.
Browse courses on Amazon Rekognition
Show steps
  • Create an Amazon Rekognition account
  • Upload a video to Amazon Rekognition
  • Index the video for faces, objects, labels, maturity content, and celebrities
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow a tutorial on deploying a web application
Deepen your understanding of deploying web applications by following a guided tutorial on using the AWS SDK to upload and index videos with Amazon Rekognition.
Show steps
  • Find a tutorial on deploying a web application with the AWS SDK
  • Follow the tutorial to deploy your own web application
  • Test your web application by uploading and indexing videos
Attend an AWS Meetup on Amazon Rekognition
Expand your knowledge of Amazon Rekognition by attending an AWS Meetup where you can connect with experts and other users.
Browse courses on Amazon Rekognition
Show steps
  • Find an AWS Meetup on Amazon Rekognition
  • Attend the Meetup and participate in discussions
  • Connect with experts and other users
Attend a workshop on Amazon Rekognition
Gain hands-on experience with Amazon Rekognition by attending a workshop where you can learn from experts and work on real-world projects.
Browse courses on Amazon Rekognition
Show steps
  • Find a workshop on Amazon Rekognition
  • Attend the workshop and participate in activities
  • Learn from experts and work on real-world projects
Contribute to an open-source project related to Amazon Rekognition
Deepen your understanding of Amazon Rekognition by contributing to an open-source project related to it.
Browse courses on Amazon Rekognition
Show steps
  • Find an open-source project related to Amazon Rekognition
  • Contribute to the project by adding features, fixing bugs, or improving documentation
  • Collaborate with other contributors
Create a video tutorial on using Amazon Rekognition
Solidify your understanding of Amazon Rekognition by creating a video tutorial on how to use it for video indexing.
Show steps
  • Plan the content of your video tutorial
  • Record your video tutorial
  • Edit and publish your video tutorial

Career center

Learners who complete Deploy a Video indexing Application using Amazon Rekognition will develop knowledge and skills that may be useful to these careers:
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course may be useful for aspiring Software Engineers as it provides hands-on experience with Amazon Rekognition, a cloud-based service for video analysis. This knowledge can be valuable in industries such as media, entertainment, and security, where video data is becoming increasingly important.
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. This course may be useful for aspiring Machine Learning Engineers as it provides hands-on experience with Amazon Rekognition, a powerful tool for video analysis. This knowledge can be valuable in industries such as healthcare, manufacturing, and transportation, where machine learning is being used to solve complex problems.
Data Analyst
A Data Analyst collects, analyzes, and interprets data to identify trends and patterns. This course may be useful for aspiring Data Analysts as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as marketing, sales, and finance, where video data is becoming increasingly important.
Data Scientist
A Data Scientist is responsible for developing and implementing data-driven solutions to business problems. This course may be useful for aspiring Data Scientists as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as healthcare, retail, and finance, where video data is becoming increasingly important.
Business Analyst
A Business Analyst helps organizations improve their performance by analyzing business processes and data. This course may be useful for aspiring Business Analysts as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as healthcare, retail, and manufacturing, where video data is becoming increasingly important.
Marketing Manager
A Marketing Manager is responsible for developing and executing marketing campaigns. This course may be useful for aspiring Marketing Managers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as media, entertainment, and retail, where video data is becoming increasingly important.
Product Manager
A Product Manager is responsible for the development and launch of new products or features. This course may be useful for aspiring Product Managers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
Customer Success Manager
A Customer Success Manager is responsible for ensuring that customers are satisfied with a company's products or services. This course may be useful for aspiring Customer Success Managers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
Sales Manager
A Sales Manager is responsible for leading a team of salespeople and achieving sales targets. This course may be useful for aspiring Sales Managers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
Project Manager
A Project Manager is responsible for planning and executing projects. This course may be useful for aspiring Project Managers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
Quality Assurance Analyst
A Quality Assurance Analyst is responsible for testing and ensuring the quality of software products. This course may be useful for aspiring Quality Assurance Analysts as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
UX Designer
A UX Designer is responsible for designing the user experience of websites and apps. This course may be useful for aspiring UX Designers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
Front-End Developer
A Front-End Developer is responsible for developing the front-end of websites and apps. This course may be useful for aspiring Front-End Developers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
UI Designer
A UI Designer is responsible for designing the user interface of websites and apps. This course may be useful for aspiring UI Designers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.
Technical Writer
A Technical Writer is responsible for creating and maintaining technical documentation. This course may be useful for aspiring Technical Writers as it provides an understanding of how to use Amazon Rekognition for video analysis. This knowledge can be valuable in industries such as technology, media, and retail, where video data is becoming increasingly important.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Deploy a Video indexing Application using Amazon Rekognition.
Provides a comprehensive overview of deep learning for computer vision, covering topics such as image classification, object detection, and semantic segmentation. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of computer vision algorithms and applications. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of computer vision algorithms and applications. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of pattern recognition and machine learning algorithms. It valuable resource for anyone interested in learning more about this field.
Provides a comprehensive overview of deep learning algorithms and applications. It valuable resource for anyone interested in learning more about this field.

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