Combine precision and recall into a single metric called the F1 score, in particular, if you need a simple way to compare classifiers.
Accuracy is not a reliable metric for the model performance, because it will yield misleading results if the validation data set is unbalanced.
The rule of thumb is to split your data across several large files. If you have too many files, the time to access each file might start getting higher.
In this tutorial, we’ll be demonstrating how to predict an image on trained keras model. So our goal has been to build a CNN
If you do not save your trained model all your model weights and values will be lost, and you would have to restart training from the beginning but if you saved your model you can always resume training.
This model capable of detecting different types of toxicity like threats, obscenity, insults, and identity-based hate.
This tutorial provides a brief explanation of the U-Net architecture as well as implement it using TensorFlow High-level API.
Very deep neural network are difficult to train because of vanishing and exploding gradients problems.
We build text classification models in Keras that use attention mechanism
Build a language model to predict the next word based on the previous word in the sequence.