Model training can take a long time. TensorFlow 2 provides the TimeStopping callback which allows stopping training after a certain amount of time has passed.
The TimeStopping callback is provided...

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TensorFlow 2 provides the CSVLogger callback which allows to write epochs results during training to a CSV file. After that file can be opened and results can be interpretated by...

TensorFlow 2 allows to count the number of trainable and non-trainable parameters of the model. It can be useful if we want to improve the model structure, reduce the size...

Mean absolute percentage error (MAPE) is a loss function that is used to solve regression problems. MAPE is calculated as the average of the absolute percentage differences between the actual...

Kaggle Dogs vs. Cats is a dataset that contains 25000 images of cats and dogs. Images are different sizes, so need them to reprocess. There are 12500 images of dogs...

Mean squared logarithmic error (MSLE) is a loss function that is used to solve regression problems. MSLE is calculated as the average of the squared differences between the log-transformed actual...

Binary classification is the process that is used to classify data points into one of two classes. For example, whether a customer will buy a product or not, emails are...

Mean absolute error (MAE) is a loss function that is used to solve regression problems. MAE is calculated as the average of the absolute differences between the actual and predicted...

CIFAR-10 is a dataset that consists of 60000 color images. The dataset is divided into 50000 training images and 10000 testing images. Each image is a 32x32 size, associated with...

Mean squared error (MSE) is a loss function that is used to solve regression problems. MSE is calculated as the average of the squared differences between the actual and predicted...