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Volver a Building Similarity Based Recommendation System

Opiniones y comentarios de aprendices correspondientes a Building Similarity Based Recommendation System por parte de Coursera Project Network

32 calificaciones

Acerca del Curso

Welcome to this 1-hour project-based course on Building Similarity Based Recommendation System. In this project, you will learn how similarity based collaborative filtering recommendation systems work, how you can collect data for building such systems. You will learn what are some different ways you to compute similarity between users and recommend items based on products interacted by other similar users. You will learn to create user item interactions matrix from the original dataset and also how to recommend items to a new user who does not have any historical interactions with the items. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

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1 - 6 de 6 revisiones para Building Similarity Based Recommendation System

por Angelina K

19 de ene. de 2021

it 's not possible to insert backets wich mach book into Jupiter notebook session the session is soo short, never 120. min, its not worth the money

por Abekah C K

5 de dic. de 2020

Very nice projects! It gave me new insights about how to solve other problems

por Kat R

6 de ago. de 2021

OK course, but an absolutely hideous implementation. You must use a virtual Windows machine in Rhyme. Rhyme is super annoying to use, and your actual workspace ends up being about the size of a mobile phone screen. It also has a session extension limit and video won't play if you click outside the tab (so you can't open a normal Jupyter Notebook and work there), it keeps switching the screens. If I wasn't desperate, I would have quit.


The course will teach you how to build a pairwise distance recommender system without external frameworks. The author often uses single lines of advanced code which can be difficult to follow if you aren't proficient in Python. This can be a nuisance or a learning opportunity, so it is up to you.


In the final quiz, the questions which you can't just copy/look up answers to in the exercise have correct answers marked with an asterisk ¯\_(ツ)_/¯ Coursera is usually better than this, so if this is your first course, don't give up.

por 61_Mayank S

12 de dic. de 2020


por DORA M B

20 de ene. de 2021

It is a good introduction to collaborative filtering.

por Wafa A

11 de oct. de 2020