CLOUD.ACADEMY.INTRODUCTION.TO.AMAZON.REKOGNITION-STM

Section

Appz

Group

STM

Size

954,89 MB

Files

23

Date

2020-03-26

NFO

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                             .:PROUDLY PRESENTS:. 

                Cloud Academy Introduction to Amazon Rekognition                

                          Release Date.: 04-09-2019 
                          Type.: Bookware 
                          Disks.: 21x50mb     
                          Link.: https://cloudacademy.com     


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                ▐█████▓▓▌       Release Notes         ▐▓▓█████▌
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       Overview
       In this course you'll learn about Amazon Rekognition, a
       service that enables you to easily and quickly integrate
       computer vision features directly into your own
       applications. At its core,áAmazon Rekognition provides an
       API that you submit images and/or videos to. You then
       instruct the Rekognition service to perform a specific
       analysis on the media. The analysis can be anything from
       detecting faces within an image to extracting labels from a
       video in an asynchronous manner.
       Lectures
       WeÆll provide in-depth reviews of the image, video, and
       collection based API sets. Amazon Rekognition makes it easy
       to add image and video analysis to your applications. You
       simply submit your image or video to the Rekognition
       service, and the service will then identify objects,
       people, text, scenes, emotions, and activities.
       Additionally the service can be used to moderate content,
       by detecting inappropriate or objectionable content.
       Demonstrations
       We finish the course with a couple of demonstrations:

       In the 1st demonstration we will show you how to use Amazon
       Rekognition together with S3 and CloudFront for hosting, to
       build a simple facial analysis static web application.
       In the 2nd demonstration we will show you how to use the
       AWSCLI to implement an object and feature detection system
       that sends an email when certain features are detected
       within an image.

       Both demonstrations will highlight the capabilities of the
       Amazon Rekognition and the different approaches you can
       adopt to interface with the service.
       Intended Audience
       The intended audience for this course includes:

       Data scientists interested in mining information from
       images and/or video
       Machine Learning enthusiasts with an interest in computer vision
       Developers interested in learning how to integrate image
       and video analysis into their own applications
       Anyone interested in learning how Amazon Rekognition works

       Learning Objectives
       By completing this course, you will:

       Understand what Amazon Rekognition is and what it offers
       Understand the benefits of using the Amazon Rekognition service
       Understand how to use Amazon Rekognition APIs to process
       both images and videos
       Understand how to use Collections and the storage based API set
       Understand business use cases and scenarios that can
       benefit from using the Amazon Rekognition service
       Be able to architect and integrate Amazon Rekognition into
       your own applications

       Pre-requisites
       The following prerequisites will be both useful and helpful
       for this course:

       General development and coding experience
       AWS S3 and IAM security experience (for the demonstrations)

       Course Agenda
       The agenda for the remainder of this course is as follows:

       WeÆll discuss what Amazon Rekognition is and when and why
       you might consider using it
       WeÆll review the Amazon Rekognition service and provide an
       in-depth review of each of its features
       WeÆll discuss benefits and business use cases that can be
       empowered by leveraging Amazon Rekognition
       WeÆll provide some example business use cases and scenarios
       that utilise the Rekognition service
       Finally - WeÆll present 2 demonstrations that highlight how
       to integrate with the Rekognition service

       Feedback
       If you have thoughts or suggestions for this course, please
       contact Cloud Academy atásupport@cloudacademy.com.



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          ▀▓▓███▀             Greetings fly out to:            ▀███▓▓▀
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         ▄▓▓█▓▓██▄            Kodemusen, KoseBamsen           ▄██▓▓█▓▓▄
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       ▄▓▓██   ▓▓██▄               STM is back.             ▄██▓▓   ██▓▓▄
      ▄▓▓██     ▓▓██▄     For all the ppl we worked with   ▄██▓▓     ██▓▓▄
     ▄▓▓██▀      ▓▓██▄     in the past. We salute you.    ▄██▓▓      ▀██▓▓▄
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    ▀▓▓█      ▐████▓▓▓▌           NFO by NiMiTech         ▐▓▓▓████▌     █▓▓▀
     ▀▓▓█▄    ▐█████▓▓▌         Updated: 09/09/2002       ▐▓▓█████▌   ▄█▓▓▀
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