Deep Learning in Practice III: Face Recognition faq

star-rating
4.4
learnersLearners: 241
instructor Instructor: Anis Koubaa instructor-icon
duration Duration: duration-icon

This course, Deep Learning in Practice III: Face Recognition, is designed to provide learners with a comprehensive introduction to face recognition with deep learning. Anis Koubaa will guide learners through the whole loop of face recognition systems, from extracting the face from an image to creating a fingerprint of the face. Learners will also learn how to develop a Python application that performs the operations. This course is essential due to the importance of face recognition systems in real-world applications. With basic knowledge of Python programming and a basic understanding of deep learning and TensorFlow, learners will be able to develop their own applications and integrate them into their projects. Don't miss this opportunity to learn the fundamentals of face recognition with deep learning!

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Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Paid

providerProvider:

Udemy

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

2023-04-18

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 27th, 2023]

This course, Deep Learning in Practice III: Face Recognition, is designed to provide learners with a comprehensive introduction to face recognition with deep learning. Anis Koubaa, the instructor, will guide learners through the entire process of face recognition systems, from extracting the face from an image and localizing the face in an image by its bounding box, to processing the extracted face through a convolutional neural network, called FaceNet in this course, to create a fingerprint of the face, which is referred to as face embedding. Learners will also learn how to develop a Python application that performs the abovementioned operations. This course is essential due to the importance of face recognition systems in real-world applications. Prerequisites for this course include basic knowledge of Python programming and a basic understanding of deep learning and TensorFlow. Upon completion of this course, learners will have a thorough understanding of the entire loop of face recognition systems and be able to develop their own applications and integrate them into their projects.

Course Syllabus

Introduction

Face Recognition: Concepts and Theoretical Background

Hands-on I: Create a face embedding using FaceNet in TF Keras

Hands-on II: Recognize a face in an image

Develop your face recognition system

Course Provider

Provider Udemy's Stats at AZClass

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faq FAQ for Face Detection Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a paid certificate. AZ Class have already checked the course certification options for you. Access the class for more details.

Q2: How do I contact your customer support team for more information?

If you have questions about the course content or need help, you can contact us through "Contact Us" at the bottom of the page.

Q3: How many people have enrolled in this course?

So far, a total of 241 people have participated in this course. The duration of this course is hour(s). Please arrange it according to your own time.

Q4: How Do I Enroll in This Course?

Click the"Go to class" button, then you will arrive at the course detail page.
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(Please note that the following steps should be performed on Udemy's official site.)
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If you're looking for additional Face Detection courses and certifications, our extensive collection at azclass.net will help you.

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