Supervised Machine Learning: Regression and Classification on Coursera

Introductions
1

Hello. I am studying the course Supervised Machine Learning: Regression and Classification on Cousera but I am unable to find the powerpoint or PDF slides that are shown in the video lecture. These are crucial for quick review and reference.

Only the subtitles in the video and the video files are available.

I urgently and sincerely request help in this matter. Thank you for any kind help.

2

Go to the Forum area for that course. You can find it in the “Course Q&A” area.
Look for its “Resources” forum.
The lecture notes are available there.

3

Thank you for replying. I am still unable to find anything like “Course Community” or “Discussion” or “Forum” among the course elements. I sincerely request help in this matter. Is there anyway I can attach a screenshot for reference?

It feels very, very discouraging to re-watch and rewind videos bit by bit instead of proper lecture notes for quick review.

I urgently request help in this matter and I shall be grateful for the same.

4

They’re here on the deeplearning.ai site. Not on Coursera.

I assume (but you did not say) which specialization you are enrolled in. But I will guess that it is the Machine Learning Specialization.

Here is a link to its forum area:

Once there, you can click on the “MLS Resources” button to find the lecture notes.

2 Likes
5

Thank you very much. I finally found the lecture notes.

I have a non-urgent question though. In the following link they say, the slides might be erroneous or lacking and it is not maintained. Is this a significant problem or will the errors or missing parts in the lecture notes be very minor and mostly insignificant?

https://community.deeplearning.ai/t/mls-course-1-lecture-notes/148503

6

Sorry, I do not know, I never use the lecture slides.

7

Sorry for delay in reply. May I request what source you use.

What would you recommend that goes with mathematical notations and overall structure used in Andrew Ng’s courses? Anything that is friendly to read and understand while being thorough in basic knowledge for job sector.

8

I watched the lectures once, studied the optional labs, and did the programming assignments and quizzes.