Building a Recommendation System in Python

===== Likes: 652 👍: Dislikes: 21 👎: 96.88% : Updated on 01-21-2023 11:57:17 EST =====
Ever wonder how the recommendation algorithms work behind large tech companies? (Facebook, Google, Apple, Netflix, Amazon etc) Look no further! I explain how the recommendation systems work and how to create your own using Matrix Factorization and Kmeans clustering.

I create a recommendation system for movies. So, stay tuned! ;)

Data Citation:
F. Maxwell Harper and Joseph A. Konstan. 2015. The MovieLens Datasets: History and Context. ACM Transactions on Interactive Intelligents Systems (TiiS) 5, 4: 19:1–19:19.

Data Link: (MovieLens)

0:00 - Why do we care about Recommendation Algorithm & System?
1:22 - Game Plan!
1:38 - Collaborative Filtering and Content-Based Filtering & Objective
3:39 - Google Collab Setup & Data
7:18 - Matrix Factorization Model Initialization & Training / Tuning Model
10:30 - Kmeans Clustering & Movie Recommendations

[nayibahued]

deepest data scientist voice in the world

[naderkhaled]

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!

[ea]

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_]

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

[Agent]

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

[icequeen]

Would love to see more of this type of video!

[folahan]

The first time I will follow a training using my own dataset and I didn't get any error from start to finish.

[ahmadjunaidi-ll]

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

[vincent_hall]

Thank you sir.
I have forked it and shall have a go collaborating with a friend.

[gauravpoudel]

Thanks for the awesome content.
BTW Is that really your voice?

[ayushthombare]

Very informative and useful video.... Thank you so much

[lo_plys]

couldn't figure out totally what he's used in this video. the only Things that I could get was that he separated the user and movies to their ratings, after this he wheighted all of them to put in a sort of a scale and then he made the predictions into clusters. Did I miss something?

[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?

[elisama]

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?

[alexhort__]

How would you do it from a real-time database, with real users?

[simyixiang]

bcs when i run the code at 9:10 in the video, the output error

[Bjorn_R]

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

[Historyiswatching]

I'm sorry I was distracted by your good looks xD

[Thunderclap]

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