04 - Binary classifier evaluation, binary Perceptron

Course website: atcold.github....

[@tantzer6113]

@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.)

[@alfcnz]

This is true _for the specific case_ of medical diagnosis. The contrary is true for other applications, such as spam detection.

[@tantzer6113]

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

[@alfcnz]

Yup, precisely! 😊😊😊

[@НиколайНовичков-е1э]

Thank you, Alfredo :)

[@alfcnz]

🤗🤗🤗

[@TemporaryForstudy]

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.

[@alfcnz]

Thanks for your appreciation! 🥰
Currently, I’m video editing and writing a textbook. Not sure these tasks are suitable for opportunities. 🥺

[@Palatino-Art]

@TemporaryForstudy
*I am from India too learning machine learning can I get your contact?*

[@CyberwizardProductions]

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

[@alfcnz]

🥳🥳🥳