Facial Expression Classification Using Residual Neural Nets

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在此指導項目中,您將:

Understand the theory and intuition behind Deep Neural Networks, and Residual Neural Networks, and Convolutional Neural Networks (CNNs).

Build and train a deep learning model based on Convolutional Neural Network and Residual blocks using Keras with Tensorflow 2.0 as a backend.

Assess the performance of trained CNN and ensure its generalization using various Key performance indicators.

Clock2 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

  • Data Science
  • Deep Learning
  • Machine Learning
  • Python Programming
  • Computer Vision

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Project Overview/Understand the problem statement and business case

  2. Import Libraries/datasets and perform preliminary data processing

  3. Perform Image Visualization

  4. Perform Image Augmentation, normalization and splitting

  5. Understand the theory and intuition behind Deep Neural Networks and CNNs

  6. Build and Train Residual Neural Network Model

  7. Assess the Performance of the Trained Model

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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