Chapter 7 – Deep Learning Foundations
- The activation function is used to introduce non-linearity to neural networks.
- The softmax function is basically a generalization of the sigmoid function. It is usually applied to the final layer of the network and while performing multi-class classification tasks. It gives the probabilities of each class being output and thus, the sum of softmax values will always equal 1.
- The epoch specifies the number of times the neural network sees our whole training data. So, we can say one epoch is equal to one forward pass and one backward pass for all training samples.
- RNNs are widely applied for use cases that involve sequential data, such as time series, text, audio, speech, video, weather, and much more. They have been greatly used in various Natural Language Processing (NLP) tasks, such as language translation, sentiment analysis, text generation, and so on.
- While backpropagating the RNN, we multiply the weights...