Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Activity

The video tutorial introduces backpropagation through time in recurrent neural networks (RNNs) and provides an activity to implement it using Numpy. The task involves coding backpropagation through time on a simple example without using auto gradient tools from deep learning frameworks. The tutorial references a previous course on convolutional networks for guidance and encourages students to complete the activity, emphasizing that taking time is normal.

What is the expected outcome of the activity described in the text?

What should a student do if the activity takes a lot of time to implement?