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Avis et commentaires pour d'étudiants pour Facial Expression Classification Using Residual Neural Nets par Coursera Project Network

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À propos du cours

In this hands-on project, we will train a deep learning model based on Convolutional Neural Networks (CNNs) and Residual Blocks to detect facial expressions. This project could be practically used for detecting customer emotions and facial expressions. By the end of this project, you will be able to: - Understand the theory and intuition behind Deep Learning, Convolutional Neural Networks (CNNs) and Residual Neural Networks. - Import Key libraries, dataset and visualize images. - Perform data augmentation to increase the size of the dataset and improve model generalization capability. - Build a deep learning model based on Convolutional Neural Network and Residual blocks using Keras with Tensorflow 2.0 as a backend. - Compile and fit Deep Learning model to training data. - Assess the performance of trained CNN and ensure its generalization using various KPIs. - Improve network performance using regularization techniques such as dropout....

Meilleurs avis

NA

29 août 2020

Wonderful course! I got a lot of new knowledge, particularly about how CNN really works and how to apply it using existing libraries in python! 6/5

EG

5 oct. 2020

the lecturer is so geniuuuuuuussss, thank you so much

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1 - 10 sur 10 Avis pour Facial Expression Classification Using Residual Neural Nets

par Nugraha S A

30 août 2020

par Endang P G

6 oct. 2020

par SYED S

27 nov. 2020

par Jesus M Z F

8 août 2020

par SASIN N

10 août 2020

par Partha B

27 sept. 2020

par Mudunuri Y V 9

29 juil. 2021

par Narendra G

30 sept. 2020

par Parag

13 févr. 2022

par Ed S

14 déc. 2020