Tensorflow and the pre-trained model can be used to compile the model with the help of the ‘compile’ method. The loss is specified as ‘BinaryCrossentropy’ in the compile parameter.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one ... Read More

Tensorflow and the pre-trained model can be used for fine tuning by setting the ‘trainable’ feature of ‘base_model’ to True. Before fine tuning, the layers are frozen.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is ... Read More

Tensorflow and the pre-trained model can be used to understand the learning curve by visualizing the operations that are performed on input dataset. The training accuracy, and validation accuracy are plotted with the help of the ‘matplotlib’ library. The training loss and validation loss are also visualized.Read More: What is ... Read More

Tensorflow and the pre-trained model can be used to see the changes during training after every epoch with the help of the ‘evaluate’ method and the ‘fit’ methods.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer ... Read More

Tensorflow and the pre-trained model can be used to compile the model by using the ‘compile’ method. Prior to this, the ‘base_learning_rate’ is also defined.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as ... Read More

Tensorflow and the pre-trained model can be used to chain data augmentation, rescaling and base model by first defining the size of the input. Once this is done, the previously defined functions namely ‘data_augmentation’, ‘base_model’ are called by passing the relevant output.Read More: What is TensorFlow and how Keras work ... Read More

Tensorflow and the pre-trained model can be used to convert features into single prediction per image by creating a ‘Dense’ layer and applying it to every image in the sequential model.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at ... Read More

Tensorflow and the pre-trained model can be used to add classification head to the model using the ‘GlobalAveragePooling2D’ method, which is assigned to a variable. This variable is used on the batch of features of the input data.Read More: What is TensorFlow and how Keras work with TensorFlow to create ... Read More

Tensorflow and the pre-trained model can be used for feature extraction by setting the ‘trainable’ feature of the previously created ‘base_model’ to ‘False’.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional ... Read More

Tensorflow and the pre-trained model can be used to convert images from one dimension to another by iterating through the image dataset and using the previously created ‘base_model’ to convert it to the required dimension.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural ... Read More