What is the purpose of reshaping the data before training the network? How is this done in TensorFlow?
Tuesday, 08 August 2023
by EITCA Academy
Reshaping the data before training the network serves a important purpose in the field of deep learning with TensorFlow. It allows us to properly structure the input data in a format that is compatible with the neural network architecture and optimizes the training process. In this context, reshaping refers to transforming the input data into
- Published in Artificial Intelligence, EITC/AI/DLTF Deep Learning with TensorFlow, Using convolutional neural network to identify dogs vs cats, Training the network, Examination review
Tagged under:
Artificial Intelligence, Data Preprocessing, Deep Learning, Neural Networks, Reshaping Data, TensorFlow