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Description
In this course, you will explore the advanced image and video analysis tools offered by Amazon Rekognition. This powerful service from AWS enables developers to easily integrate sophisticated image and video recognition capabilities into their applications. You will learn how to perform object and label detection, facial analysis, image moderation, and much more. With hands-on projects and real-world examples, this course is designed to equip you with the skills needed to work with machine learning models that can analyze and recognize objects, text, faces, and unsafe content. Whether you’re building an app with object recognition or creating systems for content moderation, this course covers everything from setup to advanced integrations.
Section 1: Introduction
This section provides a foundational overview of Amazon Rekognition. You will be introduced to the core functionalities of Rekognition and understand its capabilities in object, label, and facial recognition. By the end of this section, you’ll have a clear understanding of how Amazon Rekognition can be utilized to analyze and recognize content from images and videos.
Section 2: Object and Label Detection
The focus of this section is on Object and Label Detection, one of Rekognition’s most powerful features. You will learn how to set up Rekognition, run object and label detection, and integrate notifications when objects or labels are detected in your images. By the end of this section, you will know how to apply Rekognition to detect and classify objects in your images, as well as set up notifications for real-time processing.
Section 3: Moderation
In this section, we explore Image Moderation, which is crucial for filtering content to ensure that your application stays appropriate for all audiences. You will learn how Rekognition can be used to identify inappropriate content such as explicit material, violent images, or adult content. We will dive deeper into how this feature can be used to monitor uploaded images and videos in real-time.
Section 4: Facial Analysis
This section covers Facial Analysis in depth, including the detection of various facial attributes such as emotions, age range, gender, and facial landmarks. You will understand how to use Rekognition to analyze and interpret faces within images or videos and use this data for further processing, such as personalized recommendations or security systems.
Section 5: Advanced Rekognition Features
In the final section, we will explore advanced features of Rekognition, including:
Celebrity Rekognition: Identifying famous personalities within images and videos.
Face Comparison: Comparing two faces to determine if they belong to the same person.
Text Detection and Classification: Extracting and classifying text within images.
Detecting Unsafe Content: Leveraging Rekognition’s ability to identify unsafe content within images or videos.
Integration with AWS Lambda: Automating processes by integrating Rekognition with Lambda functions for serverless processing.
By the end of this section, you will be able to implement complex recognition tasks such as celebrity recognition, face comparison, and text classification, as well as automate workflows using AWS Lambda.
Conclusion:
By completing this course, you will gain a comprehensive understanding of Amazon Rekognition and its capabilities in object detection, facial analysis, image moderation, and more. Whether you’re building content moderation systems, face recognition applications, or implementing AI-driven photo management features, this course will provide you with the practical skills and knowledge to effectively utilize Rekognition in your projects. Get ready to dive into machine learning and computer vision with AWS Rekognition and unlock new possibilities for your applications.
| Total Students | 34 |
|---|---|
| Original Price($) | |
| Sale Price | Free |
| Number of lectures | 20 |
| Number of quizzes | 0 |
| Total Reviews | 0 |
| Global Rating | 0 |
| Instructor Name | EDUCBA Bridging the Gap |
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