@nayibahued5955

deepest data scientist voice in the world

@naderkhaled9410

Dude I know this is off topic, but ur voice is insanely satisfying !!

@AbhishekChandraShukla

Holy cow! That is a really good recommendation system! Humbling tutorial as well!

@ea1766

easily the best video on this subject, all the other videos were so boring and mundane. I wish Youtube promoted this video more to the top.

@nabila_1203

I am working on my final year project and this video is helping me understand the topic really well. Thank you for it!!!

@Agent7155

Ended up searching up for movies to watch at the end xD

@Bjorn_R

Hello Spencer im split between collaborative recommender systems and a confirmation tree project for my master thesis. What would be most beneficial?

@Thunderclap777

are there any metrics that you can use to test if what your recommending is accurate at all?

@tactical_savant01

Hi Spencer, the github link for the code is not working. can you pls resolve it. Thank you

@icequeen2778

Would love to see more of this type of video!

@vaiterius

How do you know which libraries/functions to use to make these algorithms? I’m trying to make a videogame recommendation system from a Steam games dataset, similar to what you’re doing here

@obi666

I'm not sure what these clusters are (for example Cluster #1 and printed titles), are they some sort of groups of similiar movies?

@dan7582

Nice video, keep up the good work!!

@sachamallet5157

Hi, I would like to know if the mac mini M2 pro with only 16gb of RAM is enough for 8Go of data analysis. Thank you so much for your feedback

@elisama2936

Hello! :) Ty for the video. I have a question regarding the line " def __init__(self, n_users, n_items, n_factors=20)". Can you explain why 20?

@NobixLee

Great video, but how do we then get scores for the User_ID? Something like there is this much probability that User_ID 2 will be in cluster 2? Thank you.

@vinayvajrala4366

A big like for that voice

@bhadauriaji

Hi Spencer. Was working on a similar problem where i have users who have listened to a set of songs and based on there listen history. I have to recommend new songs to the user. Almost 10. How to do that?
Also I don't have ratings for songs I have listen count for each song. And listen count is in relation to user.

@marcelomlr

Hey man, nice video, and thanks for the tutorial. I'm actually trying to build a recommendation system for online courses, like udemy, but I can't find any datasets for user reviews to make the collaborative filtering. So I decided to manually create a dataset, and thought of choosing like 4 subjects and putting some users to rate like 10-15 courses of each subject. Do you know if something like that can work, or have any tips you can give me?

@ahmadjunaidi21-l6l

Dude is not only learn deep learning but deep voice. damn