In my last two videos on TensorFlow tutorial, we worked on the basic classification and regression model. In this tutorial, we will work on some techniques to improve the TensorFlow model using Callback functions. There are several callback functions. But today we will work on two useful ones.
One is called EarlyStopping which stops the training when the specified evaluation metric is not improving anymore. So, even if you start your model training for ten thousand epochs, it will stop training if your model is not improving anymore. Another callback function we will work on today is LiveLossPlot which will keep plotting the loss function and evaluation metric for training.
Please feel free to check the TensorFlow documentation on EarlyStopping:
www.tensorflow.org/api_docs/p...
The link to the dataset for today's video:
www.kaggle.com/datasets/zalan...
Find the complete code here:
github.com/rashida048/TensorF...
The video on activation functions that mentioned in the video:
• Activation Functions -...
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