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Build a Face Recognition Solution with Microsoft Azure Face API

Few problems are as complex as Face Recognition. Usually, you have no more than a couple of images and do your best. This course will teach you how to leverage Microsoft Azure Face API for face detection and recognition with just a few lines of code

Intermediate
1h
(21)

Created by Axel Sirota

Last Updated Jul 14, 2021

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  • Course

Build a Face Recognition Solution with Microsoft Azure Face API

Few problems are as complex as Face Recognition. Usually, you have no more than a couple of images and do your best. This course will teach you how to leverage Microsoft Azure Face API for face detection and recognition with just a few lines of code

Intermediate
1h
(21)

Created by Axel Sirota

Last Updated Jul 14, 2021

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This course is included in the libraries shown below:

  • AI
  • Cloud
  • Data
What you'll learn

There are few problems as complex as Face Recognition. In this course, Build a Face Recognition Solution with Microsoft Azure Face API, you’ll gain the ability to leverage Microsoft Azure Face API for face detection and recognition with just a few lines of code. First, you’ll explore the Face API and Face Detection. Next, you’ll discover Face Recognition and finding similar faces. Finally, you’ll learn how to apply Face Similarity, Face Verification, Face Identification, and Face Grouping to your use case. When you’re finished with this course, you’ll have the skills and knowledge of Face Detection and Face Recognition in Azure needed to add those functionalities to your applications with a few lines of code.

Build a Face Recognition Solution with Microsoft Azure Face API
Intermediate
1h
(21)
Table of contents

About the author
Axel Sirota - Pluralsight course - Build a Face Recognition Solution with Microsoft Azure Face API
Axel Sirota
36 courses 3.6 author rating 1141 ratings

Axel Sirota has a Masters degree in Mathematics with a deep interest in Deep Learning and Machine Learning Operations. After researching in Probability, Statistics and Machine Learning optimization, he is currently working at JAMPP as a Machine Learning Research Engineer leveraging customer data for making accurate predictions at Real Time Bidding.

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