AIZOO Face Mask Detector using TensorFlow 2
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…
TensorFlow 2
Calculate Huber Loss using TensorFlow 2
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…
Calculate Log-Cosh Loss using TensorFlow 2
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…
Calculate Binary Cross-Entropy using TensorFlow 2
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…
Visualize Training Metrics using TensorBoard
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…
Send Epochs Results during Training to Server in TensorFlow 2
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…
Stop Training after Certain Time in TensorFlow 2
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…
Write Epochs Results during Training to CSV File in TensorFlow 2
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…
Count Number of Parameters of Model in TensorFlow 2
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…
Calculate Mean Absolute Percentage Error using TensorFlow 2
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…