What is the purpose of the testing data in the context of building a CNN to identify dogs vs cats?
Tuesday, 08 August 2023
by EITCA Academy
The purpose of testing data in the context of building a Convolutional Neural Network (CNN) to identify dogs vs cats is to evaluate the performance and generalization ability of the trained model. Testing data serves as an independent set of examples that the model has not seen during the training process. It allows us to
How can the code provided for the M Ness dataset be modified to use our own data in TensorFlow?
Tuesday, 08 August 2023
by EITCA Academy
To modify the code provided for the M Ness dataset to use your own data in TensorFlow, you need to follow a series of steps. These steps involve preparing your data, defining a model architecture, and training and testing the model on your data. 1. Preparing your data: – Start by gathering your own dataset.
- Published in Artificial Intelligence, EITC/AI/DLTF Deep Learning with TensorFlow, TensorFlow, Training and testing on data, Examination review
Tagged under:
Artificial Intelligence, Deep Learning, Model Architecture, TensorFlow, Testing Data, Training Data