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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.
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1 - 2 von 2 Bewertungen für Activity Recognition using Python, Tensorflow and Keras
von Akshat S
•16. Aug. 2022
Good project. Can be improved in the 5th lecture. Videos need to be updated. ModelCheckpoint dependency need to be imported beforehand before watching the lectures. Libraries such as cv2,os and random work only on Google Colaboratory, not on Jupyter notebook.
von Gencho Z
•6. Sep. 2022
I've not seen code written so incompetently.
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