Amazon Rekognition Development: A Complete Guide
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Amazon Rekognition Development: A Complete Guide

Learn how to add powerful visual search & image recognition capability to your applications using AWS Amazon Rekognition
5.0 (5 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
35 students enrolled
Created by Dhiman Halder
Last updated 7/2017
English
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Includes:
  • 2.5 hours on-demand video
  • 36 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Master the 6 core capabilities offered by Amazon Rekognition
  • Develop 6 complete end-to-end working solutions each featuring a different capability of Amazon Rekognition
  • Learn how to introduce Image Recognition capabilities within your own applications
  • Learn how to make Amazon Rekognition work in tandem with host of other AWS services like S3, Lambda, API Gateway, DynamoDB, ElasticSearch, SNS, Cognito, CloudWatch and IAM
View Curriculum
Requirements
  • Basic understanding of Amazon Web Services - some prior experience with S3 and Lambda Function really helps
  • Preliminary knowledge of NodeJS and HTML - a bit of coding experience doesn't hurt
  • A Windows, Mac or Linux Computer with a modern Browser, Node v6.10+ and a Code Editor Installed
  • I recommend that you follow the course from beginning to the end in the order it is laid out since some of the later projects build upon earlier ones
Description

Amazon Rekognition is a sophisticated deep learning based service from Amazon Web Services (AWS) that makes it easy to add powerful visual search and discovery to your own applications. With Rekognition using simple APIs, you can quickly detect objects, scenes, faces, celebrities and inappropriate content within images. You can also search, analyze, organize and compare faces. 

Are you a Developer looking to incorporate visual search and Image recognition capabilities to your own Applications using the recently launched Amazon Rekognition service from AWS? Are you an Architect or Tech Lead willing to explore reference Architectures and implementations on how Amazon Rekognition fits in with other AWS service offerings to solve Real-world problems? Either way, you are in the right place.

This course emphasize on learning by doing. You will be developing 6 complete end-to-end solutions with different capabilities of Amazon Rekognition. You will be developing the following projects:

  1. Deliver Dynamic Targeted Advertisement Content
  2. Intelligent Family Photo Search App 
  3. Face Based Authentication and Verification System
  4. Travel Photo Smart Search App
  5. Enhance the Travel Photo Smart Search App with Image Moderation
  6. Celebrity Recognizer

In the process, you will also interact with and learn to use the following AWS services

  1. S3
  2. Lambda Function
  3. API Gateway
  4. DynamoDB
  5. ElasticSearch
  6. Cognito
  7. SNS
  8. CloudWatch
  9. Identity and Access Management
Who is the target audience?
  • Developers interested in learning how to develop Image Recognition based applications with the Amazon Rekognition Service
  • Architects, Tech Leads willing to explore Image Recognition AI capabilities from AWS
  • Architects, Tech Leads, Developers willing to learn how to envisage complete end-to-end solutions with Amazon Rekognition and host of other allied AWS services
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Curriculum For This Course
42 Lectures
02:16:53
+
Introduction to the Course
4 Lectures 10:41

Welcome to this course on Amazon Rekognition

Preview 01:14

Introduction to Deep Learning, Amazon Rekognition Service and Demo using the AWS Management Console

Preview 05:22

You will need an AWS free tier account, A computer with a Browser, Node.js and a Code Editor installed

Preview 02:05

Getting Started with Amazon Rekognition

Getting Started
02:00
+
First Project - Deliver Dynamic Targeted Advertisement Content
8 Lectures 40:49
Introduction to the DetectFaces API
03:16

Introduction to the Project
02:02


Setup DynamoDB Table
00:53

Create a Lambda Function named "fetchad" with Node.js
07:09

Setup the "fetchad" Lambda Function and Test it
08:05

Expose an API named "advertisement" with the Amazon API Gateway
07:20

Create a Web client with HTML, JavaScript, Setup Cognito & Test
06:11
+
Second Project - Intelligent Friends & Family Photo Search App
10 Lectures 36:16
Introduction to Face Recognition APIs and the Project
04:48

Create a S3 Bucket
01:28


Create a HTML Web Client and Test it
02:28

Create another S3 Bucket
01:03

Create another Lambda Function "searchfaces" for searching "ALL" faces
08:53

Setup the "searchfaces" Lambda Function and Test it
04:13

Expose a "picturealbum" API with Amazon API Gateway
04:06

Enhance the Web Client to Allow Searches
01:49

Use the Enhanced Web Client to perform Searches
02:46
+
Third Project - Face Based Authentication and Verification System
6 Lectures 16:07

Create S3 bucket
02:07

Create a "verifyface" Lambda Function
01:31

Create an IAM role
02:30

Setup the "verifyface" Lambda Function and Test it
01:32

Setup Cognito Identity Pool, Create Web Client and Test it
05:29
+
Fourth Project - Travel Photo Smart Search App
10 Lectures 23:31
Introduction to the DetectLabels API and the Project
06:09

Create Amazon ElasticSearch Domain
01:06

Create S3 bucket
00:44

Create the "indexlabels" Lambda Function
03:06

Setup the "indexlabels" Lambda Function and Test it
02:49

Create the "searchlabels" Lambda Function
01:45

Setup the "searchlabels" Lambda Function and Test it
01:05

Expose a "travel" API with Amazon API Gateway
02:19

Create a Web Client to perform Searches
02:22

+
Fifth Project - Add Image Moderation to Travel Photo Smart Search App
2 Lectures 06:36
Introduction to the DetectModerationLabels API and the Project
03:28

Setup Cognito Identity Pool, Create Web Client and Test it
03:08
+
Sixth Project - Celebrity Recognizer
2 Lectures 02:53
Introduction to the RecognizeCelebrities API and the Project
01:04

Create Web Client and Test it
01:49
About the Instructor
Dhiman Halder
5.0 Average rating
5 Reviews
35 Students
1 Course
Architect

I am a Solutions Architect with 14 years of IT experience - with 6+ years working with the AWS platform. I am an AWS Certified Solutions Architect as of 2015. I have a lot of experience Architecting & Developing Scalable Fault tolerant distributed systems. I specialize in the e-commerce domain. My forte is .Net and AWS.