TensorBoard is a tool which allows visualizing training metrics (e.g. loss and accuracy), model graph, activation histograms, profiling results, etc. This tutorial demonstrates how to visualize training metrics using TensorBoard...

When working with ESP8266 we may need to be able to discover surrounding Wi-Fi networks. This tutorial provides example how to scan the available Wi-Fi networks using ESP8266 NodeMCU development...

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...

SHA-256 is a cryptographic hash function that accepts a string of any length and returns a 256-bit fixed-length digest value, commonly represented as a sequence of 64 hexadecimal digits. SHA-256...

MD2 is a cryptographic hash function that accepts a string of any length and returns a 128-bit fixed-length digest value, commonly represented as a sequence of 32 hexadecimal digits. MD2...

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...

The ESP8266 can operate on station (STA) mode. It means that ESP8266 can connect to an existing Wi-Fi network. ESP8266 gets IP address from wireless router and can start to...

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...