04 - Binary classifier evaluation, binary Perceptron 

Thank you, Alfredo :)

@5:24 Paraphrase: "So, what is the accuracy of a classifier that classifies everything as HAM, detecting no SPAM, thus yielding NO POSITIVES ?"

@14:04 Paraphrase: Missing a positive (i.e., false negative) is more critical (i.e., worse) than a FALSE POSITIVE. (Note: "falsely identify a negative case" means "falsely identify AS A POSITIVE what is actually a negative case.)

Loved the video ❤. hey i am working as an nlp engineer in india. do you have any remote opportunities for me? let me know if you have something.

that's the entire reason to teach :) learn how to do something and pass it on