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Developing Applications with AWS Rekognition

Alan Jones

One of the hot topics in artificial intelligence today is image analysis. This course will help you understand how to leverage the AWS services for image and video processing in your applications.

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One of the hot topics in artificial intelligence today is image analysis. This course will help you understand how to leverage the AWS services for image and video processing in your applications.

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.

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What's inside

Syllabus

Course Overview
Introduction to Rekognition
Using the Image Features of Rekognition
Using the Video Features of Rekognition
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Building a Complete Rekognition Application
Conclusion

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops image and video recognition skills, which are core skills for developing modern software applications
Taught by Alan Jones, who are recognized for their work in image analysis
Explores Rekognition, which is standard in industry for image analysis
Provides hands-on labs and interactive materials for learners to practice their skills
Teaches essential concepts of image analysis, which are highly relevant to machine learning and artificial intelligence

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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 Developing Applications with AWS Rekognition with these activities:
Review general concepts and techniques in computer vision and image processing
Enhance your understanding of the fundamental principles underlying image recognition.
Browse courses on Computer Vision
Show steps
  • Review introductory materials on computer vision and image processing concepts, such as image representation, feature extraction, and classification techniques.
  • Solve practice problems or exercises to reinforce your understanding.
Review course syllabus and material list
Get organized for your learning journey.
Show steps
  • Access the course syllabus and material list from the online portal.
  • Read the syllabus carefully and note the required textbooks, software, and other materials.
  • Gather any necessary physical materials, such as textbooks, from the bookstore or library.
  • Set up a dedicated study space where you can access the online portal, materials, and software.
Follow online video tutorials on AWS Rekognition basics
Get comfortable working with AWS Rekognition before diving deep into the course content.
Show steps
  • Search for free online video tutorials on AWS Rekognition.
  • Identify tutorials covering basic concepts, such as object detection and facial recognition.
  • Follow along with the tutorials, taking notes and practicing the demonstrated techniques.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Connect with a mentor in the field of image recognition or cloud computing
Gain personalized guidance and support from an experienced professional.
Show steps
  • Identify potential mentors through personal connections, professional networking, or online platforms.
  • Reach out to mentors and introduce yourself, expressing your interest in mentorship.
  • Schedule a meeting or call to discuss your career goals and areas where you seek guidance.
  • Establish a regular communication schedule and agenda for mentorship sessions.
Practice using the AWS SDK for Rekognition
Build your confidence working with the AWS SDK for Rekognition by practicing regularly.
Show steps
  • Install the AWS SDK for Rekognition in your preferred development environment.
  • Find practice problems or exercises that involve using the AWS SDK for Rekognition.
  • Solve the practice problems, using the AWS documentation as a reference.
Attend a local meetup or online event focused on AWS and cloud computing
Connect with industry professionals and learn about the latest trends in image recognition.
Show steps
  • Find local meetups or online events related to AWS and cloud computing.
  • Register for the event and prepare to actively participate.
  • Attend the event, engage in discussions, and exchange knowledge with others.
Create a collection of resources on AWS Rekognition and image recognition
Consolidate and organize your learning resources for easy future reference.
Show steps
  • Gather resources from the course, online tutorials, documentation, and other relevant sources.
  • Organize the resources into a structured format, such as a shared document, online folder, or wiki.
  • Include resources covering various aspects of image recognition, such as object detection, facial analysis, and video processing.
  • Optionally, share the compilation with other learners or the community.
Build a simple image processing application using Rekognition
Apply your Rekognition skills by creating a practical project.
Show steps
  • Design a simple image processing application that utilizes Rekognition features.
  • Choose a programming language and development environment for your application.
  • Implement the application's functionality using the AWS Rekognition SDK.
  • Test and debug your application to ensure it meets the desired requirements.
  • Optionally, deploy your application to a cloud platform or share it with others.
Participate in an online coding or hackathon challenge related to image recognition
Test and showcase your skills while learning from others in the field.
Show steps
  • Find online coding or hackathon challenges related to image recognition.
  • Register for the challenge and form a team, if necessary.
  • Work on the challenge, applying your Rekognition knowledge and problem-solving abilities.
  • Submit your solution and await the results.
  • Reflect on your experience and identify areas for improvement.

Career center

Learners who complete Developing Applications with AWS Rekognition will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, deploying, and maintaining machine learning models. This course can be useful for Machine Learning Engineers who want to learn how to use AWS Rekognition to build image and video processing applications. It can help them understand the capabilities of this service and how to use it to solve real-world problems.
Software Engineer
Software Engineers design, develop, test, and maintain software systems. This course can be useful for Software Engineers who want to learn how to use AWS Rekognition to build image and video processing applications. It can help them understand the capabilities of this service and how to use it to solve real-world problems.
Sales Manager
Sales Managers plan and execute sales strategies. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Sales Managers understand how to use this technology to improve sales performance.
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Data Scientists understand how to use this technology to build applications that can analyze images and videos for various purposes.
Business Analyst
Business Analysts analyze business processes and systems to identify opportunities for improvement. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Business Analysts understand how to use this technology to analyze images and videos for various purposes, such as identifying customer trends or improving product design.
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Data Analysts understand how to use this technology to analyze images and videos for various purposes.
Product Manager
Product Managers plan and execute the development and marketing of products. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Product Managers understand how to use this technology to develop products that meet the needs of customers.
Computer Scientist
Computer Scientists research, design, develop, and implement computer systems and applications. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Computer Scientists understand how to use this technology to build applications that can analyze images and videos for various purposes.
Technical Writer
Technical Writers create documentation for software products. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Technical Writers understand how to use this technology to create documentation for image and video processing applications.
Customer Success Manager
Customer Success Managers ensure that customers are satisfied with a company's products and services. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Customer Success Managers understand how to use this technology to improve customer satisfaction.
Computer Vision Engineer
Computer Vision Engineers plan and execute projects related to computer-based image analysis and modeling, enhancing the utility of computer vision technology. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Computer Vision Engineers understand how to use this technology to build applications that can analyze images and videos for various purposes.
Quality Assurance Analyst
Quality Assurance Analysts test and evaluate software products to ensure that they meet quality standards. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Quality Assurance Analysts understand how to use this technology to test and evaluate image and video processing applications.
Marketing Manager
Marketing Managers plan and execute marketing campaigns. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Marketing Managers understand how to use this technology to create marketing campaigns that are more effective.
Support Engineer
Support Engineers provide technical support to customers. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Support Engineers understand how to use this technology to resolve customer issues.
Project Manager
Project Managers plan, execute, and close projects. This course may be useful as it provides a foundation in the use of AWS Rekognition for image and video processing. It can help Project Managers understand how to use this technology to manage projects related to image and video processing.

Reading list

We've selected ten 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 Developing Applications with AWS Rekognition.
Provides a comprehensive overview of pattern recognition, including supervised and unsupervised learning. It great resource for those who want to understand how AWS Rekognition uses machine learning to identify objects and faces.
Covers the fundamentals of deep learning, including convolutional neural networks, recurrent neural networks, and unsupervised learning. It great resource for anyone who wants to learn more about the theory and practice of deep learning.
Provides hands-on experience with OpenCV, a leading library for computer vision. It great resource for those who want to learn how to use AWS Rekognition in real-world applications.
Provides a comprehensive overview of computer vision. It great resource for those who want to understand the fundamentals of computer vision as it relates to AWS Rekognition.
Provides a comprehensive overview of artificial intelligence for computer vision. It great resource for those who want to understand how AWS Rekognition uses artificial intelligence to identify objects and faces.
Provides a comprehensive overview of computer vision technology for food quality evaluation. It great resource for those who want to understand how AWS Rekognition can be used to improve the quality of food products.
This classic textbook on digital image processing. It covers a wide range of topics, including image enhancement, restoration, and segmentation. It great resource for those who want to understand the fundamentals of image processing as it relates to AWS Rekognition.

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