Activity Recognition using Python, Tensorflow and Keras

oferecido por
Coursera Project Network
Neste Projeto Guiado, você irá:

Learn about data augmentation.

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

Clock1.5 hours
BeginnerBásico
CloudSem necessidade de download
VideoVídeo em tela dividida
Comment DotsInglês
LaptopApenas em desktop

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 você desenvolverá

Deep LearningPython ProgrammingTensorflowcognitive data sciencekeras

Aprender passo a passo

Em um vídeo reproduzido em uma tela dividida com a área de trabalho, seu instrutor o orientará sobre esses passos:

  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.

Como funcionam os projetos guiados

Sua área de trabalho é um espaço em nuvem, acessado diretamente do navegador, sem necessidade de nenhum download

Em um vídeo de tela dividida, seu instrutor te orientará passo a passo

Perguntas Frequentes – FAQ

Perguntas Frequentes – FAQ

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