Activity Recognition using Python, Tensorflow and Keras

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Activity Recognition using Python, Tensorflow and Keras provided by Coursera is a comprehensive online course, which lasts for 1-2 hours worth of material. Activity Recognition using Python, Tensorflow and Keras is taught by Vinita Silaparasetty. Upon completion of the course, you can receive an e-certificate from Coursera. The course is taught in Englishand is Paid Course. Visit the course page at Coursera for detailed price information.

Overview
  • 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.