ONNX is a format for representing machine learning models. ONNX Runtime can be used to run inference using model represented in ONNX format.
This tutorial demonstrates how to convert TensorFlow...
TensorFlow 2
TensorFlow 2 provides the TFLiteConverter which allows to convert a TensorFlow 2 model to TensorFlow Lite model. This model uses the .tflite file extension. TensorFlow Lite models can be executed...
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...