Week 3 assignment clarification and additional supporting materials


I have just finished the week 3 assignment and it was really interesting. Kind of putting all the skills together. However, there are some clarifications I need to make to make sure I understand some coding before moving forward. Kindly find the snippets below:

code 1:
model_predict_r = lambda Xl: np.argmax(tf.nn.softmax(model_r.predict(Xl)).numpy(),axis=1)

question: what does “lambda XI:” do?

code 2:

import logging

question: I presume this code has to do with catching errors. But what errors?

code 3:

print(f"Finished lambda = {lambda_}")

question: the Iterate to find the optimal regularization value prints the value of “lambda” as indicated above. It will be great to be able to print out the “lambda” along with the last “loss value” and the lowest “loss value” along with the corresponding “epochs”. I.e., How do I access the “loss values”?

Lastly, I will really appreciate a video reference material to review Plotting, Tensorflow and Keras. Especially Plotting, because it is critical to understand what is happening under the hood of all these models as demonstrated in this lecture. I feel it is important to be versatile in pyplot.

What an exciting lecture series!! :smile:

Repeated. See Help with resources for python plotting lectures