Activity Recognition using Python, Tensorflow and Keras

ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

Learn about data augmentation.

Learn about transfer learning using training the pre-trained model InceptionNet V3 on the data.

Clock1.5 hours
BeginnerPrincipiante
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

Note: The rhyme platform currently does not support webcams, so this is not a live project. This guided project is about human activity recognition using Python,TensorFlow2 and Keras. Human activity recognition comes under the computer vision domain. In this project you will learn how to customize the InceptionNet model using Tensorflow2 and Keras. While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning. Special Feature: 1.Manually label images. 2. Learn how to use data augmentation normalization. 3. Learn about transfer learning using training the pre-trained model InceptionNet V3 on the data. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que desarrollarás

  • Deep Learning
  • Python Programming
  • Tensorflow
  • cognitive data science
  • keras

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. Learn how to normalize data to improve accuracy of the final results.

  2. Learn how to fine tune the model to improve it's accuracy.

  3. Learn how to apply transfer learning using InceptionNet V3.

  4. Learn how to augment data to prevent overfitting of the model.

  5. Learn how to label data manually as 0 or 1.

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

Preguntas Frecuentes

Preguntas Frecuentes

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