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Recognizing Facials and Objects with Amazon Rekognition

Rogerio Guimaraes

In this two hours project, you understand how Amazon Rekognition works and will learn how to use the AWS SDK to Analyze Faces, detect objects and labels in image scenes, moderate images, identify celebrities and recognize and compare faces using Artificial Intelligence.

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

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

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What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Relevant to industry by using AWS SDK to analyze images with high confidence and low costs
Includes a practical project to apply the concepts learned
Suitable for learners with no prior experience in Amazon Rekognition
May require additional resources or knowledge to fully understand the concepts

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Reviews summary

Practical amazon rekognition overview

According to learners, this course offers a practical and hands-on introduction to Amazon Rekognition, focusing on its core features like facial and object detection. Many found it a clear and quick way to grasp the AWS SDK for AI, enabling them to analyze images efficiently. However, some experienced it as fast-paced, and prospective students should be aware that it may assume some prior AWS familiarity, potentially leading to environment setup challenges for absolute beginners. It's considered a strong primer for developers but might lack deep dives into advanced topics or comprehensive troubleshooting.
Offers a concise and focused introduction to key Rekognition functions.
"In just two hours, I understood how to use Rekognition for facial detection and object labeling."
"Excellent way to get started with AI on AWS. The walkthrough was very helpful for quick learning."
"It's a fantastic primer for anyone looking to add AI image analysis to their skills rapidly."
Provides direct, hands-on experience with Amazon Rekognition.
"Great hands-on introduction to Rekognition. The steps were clear and I got a working example quickly."
"This project delivered exactly what it promised: a quick, practical guide to Amazon Rekognition features."
"I was able to use Amazon Rekognition to analyze my own images in just a few steps once the project was done."
Good for basics but lacks advanced topics or comprehensive troubleshooting.
"Too superficial; I couldn't apply it to specific use cases without significant additional research."
"Covered the advertised features but didn't go deep into any advanced topics or troubleshooting common errors."
"I wish there was more explanation of *why* certain steps were taken, not just *how* to do them."
Assumes some prior familiarity with AWS, potentially challenging new users.
"If you're completely new to AWS, you might struggle a bit with the setup, though the Rekognition part itself is clear."
"I spent more time debugging environment issues than learning Rekognition, as it assumes too much AWS knowledge."
"Managing AWS credentials and permissions was a bit of a hurdle for me, but the core Rekognition API usage was clear."

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 Recognizing Facials and Objects with Amazon Rekognition with these activities:
Review Course Materials and Resources
回顾课程材料，增强对 Amazon Rekognition 的理解。
Show steps
  • Read the course syllabus and lecture notes
  • Review the provided code samples
  • Explore additional resources recommended by the instructor
Attend an Amazon Rekognition Workshop or Meetup
通过参加活动，了解 Amazon Rekognition 的最新动态并与专家交流。
Browse courses on Amazon Rekognition
Show steps
  • Search for upcoming events
  • Register for the event
  • Attend the event and actively participate
  • Follow up with speakers or attendees
Discuss and Solve Amazon Rekognition Challenges
与同学合作解决有关 Amazon Rekognition 的挑战，巩固你的理解。
Browse courses on Amazon Rekognition
Show steps
  • Form a study group or find a peer to collaborate with
  • Identify a specific challenge or problem
  • Brainstorm and discuss potential solutions
  • Present your findings to the group or class
Three other activities
Expand to see all activities and additional details
Show all six activities
Demo Amazon Rekognition Services
熟悉 Amazon Rekognition 的服务并了解其功能。
Browse courses on Amazon Rekognition
Show steps
  • Access Amazon Rekognition Console
  • Explore the available services
  • Demoat least one service
Practice Using Amazon Rekognition SDK
通过动手练习，提升使用 Amazon Rekognition SDK 的能力。
Browse courses on AWS SDK
Show steps
  • Set up AWS credentials and environment
  • Install the Amazon Rekognition SDK
  • Implement sample code to use the SDK
  • Troubleshoot any errors
Contribute to Amazon Rekognition Open Source Projects
通过参与开放源码项目，深入了解 Amazon Rekognition 并为社区做出贡献。
Browse courses on Amazon Rekognition
Show steps
  • Identify a suitable open source project
  • Familiarize yourself with the project codebase
  • Propose and implement a code contribution
  • Submit a pull request

Career center

Learners who complete Recognizing Facials and Objects with Amazon Rekognition will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Develop and implement machine learning solutions to solve complex business problems. Design and build machine learning models to automate tasks, improve decision-making, and gain insights from data. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and deploy machine learning models that leverage facial recognition and object detection.
See salaries and explore the career path for Machine Learning Engineer
Software Development Engineer
Develop, update, and maintain software applications used to support various business functions. Use a variety of programming languages to ensure the quality and functionality of software products. By taking this course, you will gain the necessary skills and knowledge to use Amazon Rekognition and other AWS services to build and maintain applications that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Software Development Engineer
Data Scientist
Extract and analyze data to help businesses use information to make better decisions. Work with large datasets to identify patterns and trends. This course provides a solid foundation in using Amazon Rekognition to analyze and interpret visual data, which is a valuable skill for data scientists who work with image or video data.
See salaries and explore the career path for Data Scientist
Business Analyst
Analyze business processes and data to identify areas for improvement. Develop and implement solutions to improve efficiency and productivity. This course provides a valuable foundation in using Amazon Rekognition to analyze images and extract insights, which can be applied to improve business processes and inform decision-making.
See salaries and explore the career path for Business Analyst
Marketing Analyst
Analyze marketing data to measure the effectiveness of marketing campaigns. Use data to identify trends and opportunities. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to analyze images and videos to extract insights, which can be applied to improve marketing campaigns and measure their effectiveness.
See salaries and explore the career path for Marketing Analyst
Solutions Architect
Design and implement cloud computing solutions. Work with customers to understand their needs and develop solutions that meet those needs. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and maintain cloud-based solutions that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Solutions Architect
Data Analyst
Analyze data to identify trends and patterns. Use data to make recommendations and improve business processes. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to analyze and interpret visual data, which is a valuable skill for data analysts who work with image or video data.
See salaries and explore the career path for Data Analyst
Project Manager
Plan and manage software development projects. Work with stakeholders to ensure that projects are delivered on time and within budget. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and maintain software products that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Project Manager
Product Owner
Define the vision and roadmap for software products. Work with engineers and other stakeholders to ensure that products are developed according to the vision. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and maintain software products that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Product Owner
Product Manager
Develop and manage software products. Work with engineers, designers, and marketers to bring new products to market. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to enhance your products with facial recognition and object detection capabilities, providing a better user experience.
See salaries and explore the career path for Product Manager
Salesforce Administrator
Configure and manage Salesforce software to meet the needs of a business. Work with users to ensure they are using the software effectively. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to integrate with Salesforce and enhance the platform with visual recognition capabilities.
See salaries and explore the career path for Salesforce Administrator
Software Engineer
Design, develop, and maintain software applications. Work with users to understand their needs and develop solutions that meet those needs. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and maintain applications that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Software Engineer
Data Engineer
Design and build data pipelines to process and store data. Work with data scientists and other engineers to ensure that data is available in a timely and reliable manner. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and maintain data pipelines that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Data Engineer
Full-Stack Developer
Design, develop, and maintain web applications. Work with both the front-end and back-end of applications. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and maintain web applications that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Full-Stack Developer
Engineering Manager
Manage teams of engineers and oversee the development of software products. Work with stakeholders to ensure that products are delivered on time and within budget. This course will help you gain the necessary skills and knowledge to use Amazon Rekognition to build and maintain software products that leverage machine learning and artificial intelligence.
See salaries and explore the career path for Engineering Manager

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 Recognizing Facials and Objects with Amazon Rekognition.
Cover image
Concurrent NumPy in Python
Save
Provides a comprehensive overview of deep learning for computer vision. It covers topics such as image classification, object detection, and facial analysis. The book also includes hands-on exercises that show you how to build and deploy deep learning models for computer vision tasks.
Concurrent NumPy in Python: Faster NumPy With BLAS,...
Paperback
$$
Concurrent NumPy in Python: Faster NumPy With BLAS,...
Kindle Edition
$$
Cover image
Computer Vision
Save
Provides a comprehensive overview of computer vision algorithms and applications. It covers topics such as image formation, image processing, and object recognition. The book valuable resource for anyone who wants to learn more about computer vision.
Computer Vision
Paperback
Check
Computer Vision
Kindle Edition
Check
Pattern Recognition and Machine Learning
Save
Provides a comprehensive overview of pattern recognition and machine learning. It covers topics such as statistical learning, Bayesian inference, and support vector machines. The book valuable resource for anyone who wants to learn more about pattern recognition and machine learning.
Pattern Recognition and Machine Learning...
Hardcover
$$$
Pattern Recognition and Machine Learning...
Paperback
$$$
Pattern Recognition and Machine Learning (text...
Unknown Binding
$$$$
Cover image
Reinforcement Learning, second edition
Save
Provides a comprehensive overview of reinforcement learning. It covers topics such as Markov decision processes, value functions, and policy gradients. The book valuable resource for anyone who wants to learn more about reinforcement learning.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Cover image
Deep Learning
Save
Provides a comprehensive overview of generative adversarial networks. It covers topics such as GAN architectures, training algorithms, and applications. The book valuable resource for anyone who wants to learn more about generative adversarial networks.
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Probability and Statistics for Computer Science
Save
Provides a comprehensive overview of computer vision. It covers topics such as image formation, image processing, and object recognition. The book valuable resource for anyone who wants to learn more about computer vision.
Probability and Statistics for Computer Science
Paperback
$$$
Probability and Statistics for Computer Science
Kindle Edition
$$$

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Course image
Effort
2 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Rogerio Guimaraes
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Relevant to industry by using AWS SDK to analyze images with high confidence and low costs
Includes a practical project to apply the concepts learned
Suitable for learners with no prior experience in Amazon Rekognition
May require additional resources or knowledge to fully understand the concepts
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