https://github.com/anas436/content-based-movie-recommendation-system-with-python
https://github.com/anas436/content-based-movie-recommendation-system-with-python
jupyterlab math matplotlib-pyplot numpy pandas python3
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/anas436/content-based-movie-recommendation-system-with-python
- Owner: Anas436
- Created: 2022-09-09T16:58:16.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-09-10T18:33:16.000Z (almost 4 years ago)
- Last Synced: 2025-03-27T10:48:08.575Z (about 1 year ago)
- Topics: jupyterlab, math, matplotlib-pyplot, numpy, pandas, python3
- Language: Jupyter Notebook
- Homepage:
- Size: 699 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Content-Based-Movie-Recommendation-System-with-Python
## Objectives
After completing this lab you will be able to:
* Create a recommendation system using Content Based filtering
Recommendation systems are a collection of algorithms used to recommend items to users based on information taken from the user. These systems have become ubiquitous, and can be commonly seen in online stores, movies databases and job finders. In this notebook, we will explore Content-based recommendation systems and implement a simple version of one using Python and the Pandas library.
### Table of contents
Now, let's take a look at how to implement **Content-Based** or **Item-Item recommendation systems**. This technique attempts to figure out what a user's favourite aspects of an item is, and then recommends items that present those aspects. In our case, we're going to try to figure out the input's favorite genres from the movies and ratings given.
__Dataset__: Dataset acquired from [GroupLens](https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-ML0101EN-SkillsNetwork/labs/Module%205/data/moviedataset.zip)