Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.48 GB | Duration: 3h 3m
Learn to leverage Amazon Rekognition's powerful image and video analysis capabilities.
What you'll learn
Amazon Rekognition Fundamentals: Understand the core capabilities of Amazon Rekognition, including object detection, label recognition, and facial analysis.
Object and Label Detection: Perform real-time object and label detection in images and videos.
Image Moderation: Use Rekognition to filter inappropriate or sensitive content in images.
Facial Analysis: Analyze facial attributes like age, emotions, and gender.
Advanced Rekognition Features: Implement celebrity recognition to identify famous personalities.
AWS Integration and Automation: Integrate Rekognition with AWS Lambda for serverless automation.
Hands-on Projects: Gain practical experience through hands-on projects like building a smart image moderation system and setting up a face recognition app.
Requirements
Basic Understanding of AWS: Familiarity with AWS services, particularly IAM, S3, and Lambda, is recommended.
Programming Knowledge: Basic to intermediate skills in Python programming are essential, as the course involves writing scripts to interact with AWS Rekognition.
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: IntroductionThis 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 DetectionThe 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: ModerationIn 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 AnalysisThis 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 FeaturesIn 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.
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Object and Label Detection
Lecture 2 Amazon Rekognition
Lecture 3 Rekognition Set Up
Lecture 4 Object and Label Detection
Lecture 5 Object and Label Detection Continue
Lecture 6 Object and Label Detection with Notification
Section 3: Moderation
Lecture 7 Image Moderation
Lecture 8 Image Moderation Continue
Section 4: Facial Analysis
Lecture 9 Facial Analysis Part 1
Lecture 10 Facial Analysis Part 2
Lecture 11 Facial Analysis Part 3
Section 5: Rekognition
Lecture 12 Celebrity Rekognition
Lecture 13 Face Comparison
Lecture 14 Text Detection and Classification
Lecture 15 Object
Lecture 16 Label Detection
Lecture 17 Detect Unsafe Content
Lecture 18 Celebrity Recognition
Lecture 19 Face Detection
Lecture 20 Lambada Function
Data Scientists and AI Enthusiasts: Those who are eager to explore how AI and machine learning can be applied to image and video analysis.,Cloud Engineers and Solution Architects: Cloud professionals who want to integrate AWS Rekognition into their cloud solutions for image recognition, object detection, and facial analysis.,Developers and Programmers: Python developers interested in expanding their knowledge of AWS services and applying them to real-world use cases.,IoT and Smart Device Developers: Engineers looking to integrate IoT devices with AWS Rekognition for innovative projects like smart surveillance, automated monitoring systems, or IoT-based security solutions.,Digital Forensics and Security Analysts: Professionals in security, digital forensics, and compliance who want to use AI-powered tools for detecting unsafe content, image moderation, and facial recognition.,Students and Tech Enthusiasts: University students, tech enthusiasts, and self-learners interested in hands-on experience with AWS Rekognition for projects and research.,Business Analysts and Product Managers: Business professionals looking to leverage AI for improving product offerings in areas such as customer identification, automated content moderation, or enhancing user experiences through image and video analytics.
Screenshots
Say "Thank You"
rapidgator.net:
News
Site map
SitemapIndex
RSS Feed