Coronavirus (COVID-19) has affected many countries around the world. One of the protection method is to wear a face mask in public spaces. Many service providers and event organisers require…
Huber loss is a loss function that is used to solve regression problems. This function is a combination of the mean squared error (MSE) and mean absolute error (MAE). Huber…
Log-cosh loss is a loss function that is used to solve regression problems. Log-cosh is calculated as the average logarithm of the hyperbolic cosine of the differences between the predicted…
Binary cross-entropy (BCE) is a loss function that is used to solve binary classification problems (when there are only two classes). BCE is the measure of how far away from…
TensorBoard is a tool which allows to visualize training metrics (e.g. loss and accuracy), model graph, activation histograms, profiling results, etc. This tutorial demonstrates how to visualize training metrics using…
TensorFlow 2 provides the RemoteMonitor callback which allows to send epochs results during training to a server. A server can save results to a file, database table or perform other…
Model training can take a long time. TensorFlow 2 provides the TimeStopping callback which allows to stop training after a certain amount of time has passed. The TimeStopping callback is…
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…