Deep Learning in Practice III: Face Recognition

Course Feature

Cost

Paid
Provider

Udemy
Certificate

Paid Certification
Language

English
Start Date

2023-04-18
Learners

No Information
Duration

No Information
Instructor

Anis Koubaa

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4.4

241 Ratings

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 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

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