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Comentários e feedback de alunos de Facial Expression Classification Using Residual Neural Nets da instituição Coursera Project Network

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Sobre o curso

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....

Melhores avaliações

NA

29 de ago de 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 de out de 2020

the lecturer is so geniuuuuuuussss, thank you so much

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1 — 10 de 10 Avaliações para o Facial Expression Classification Using Residual Neural Nets

por Nugraha S A

30 de ago de 2020

por Endang P G

6 de out de 2020

por SYED S

27 de nov de 2020

por Jesus M Z F

8 de ago de 2020

por SASIN N

10 de ago de 2020

por Partha B

27 de set de 2020

por Mudunuri Y V 9

29 de jul de 2021

por Narendra G

30 de set de 2020

por Parag

13 de fev de 2022

por Ed S

14 de dez de 2020