Emotion AI: Facial Key-points Detection

4.6
estrellas
143 calificaciones
ofrecido por
Coursera Project Network
6812 ya inscrito
En este proyecto guiado, tú:

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.

Clock3 hours
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

In this 1-hour long project-based course, 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.

Habilidades que desarrollarás

  • Deep Learning
  • Machine Learning
  • Python Programming
  • Artificial Intelligence(AI)
  • Computer Vision

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

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

  2. Task 2: Import Libraries/datasets and perform preliminary data processing

  3. Task 3: Perform Image Visualization

  4. Task 4: Perform Image Augmentation

  5. Task 5: Prepare the data for deep learning model training (Normalization/reshaping)

  6. Task 6: Understand the theory and intuition behind Deep Neural Networks and CNNs.

  7. Task 7: Build Deep Residual Neural Network Model

  8. Task 8: Compile and train deep learning model

  9. Task 9: Assess the Performance of the Trained Model

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Instructor

Reseñas

Principales reseñas sobre EMOTION AI: FACIAL KEY-POINTS DETECTION

Ver todas las reseñas

Preguntas Frecuentes

Preguntas Frecuentes

¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.