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https://github.com/codewithcharan/anime-recommender-streamlit-app
https://github.com/codewithcharan/anime-recommender-streamlit-app
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/codewithcharan/anime-recommender-streamlit-app
- Owner: CodeWithCharan
- License: mit
- Created: 2024-01-30T18:10:56.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-02-07T11:20:00.000Z (12 months ago)
- Last Synced: 2024-02-07T12:38:10.088Z (12 months ago)
- Language: Jupyter Notebook
- Size: 28.8 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Anime-Recommendation-System
In this project, I've built an anime recommendation system to individual preferences. Just type your favorite anime in the search box and it will give you a list of anime recommendations based on your preferences like type (TV, OVA, etc), genre (Fantasy, Action, etc) and other features.
To achieve this, I performed various tasks, including Data cleaning, Feature engineering, Exploratory Data Analysis (EDA), Data preprocessing, Collaborative filtering, Content-based filtering and Model development.
## Video Presentation
https://github.com/CodeWithCharan/Anime-Recommender-Streamlit-App/assets/106027109/7fc498af-aa98-46e6-a76f-494b708e6237
## DATASET
This dataset is taken from : https://www.kaggle.com/CooperUnion/anime-recommendations-database?select=anime.csv
### Anime.csv
1. anime_id - myanimelist.net's unique id identifying an anime.
2. name - full name of anime.
3. genre - Action, Fantasy, Hentai, etc.
4. type - movie, TV, OVA, etc.
5. episodes - how many episodes in this show. (1 if movie).
6. rating - average rating out of 10 for this anime.
7. members - number of community members that are in this anime's "group".
### Rating.csv
1. user_id - non identifiable randomly generated user id.
2. anime_id - the anime that this user has rated.
3. rating - rating out of 10 this user has assigned (-1 if the user watched it but didn't assign a rating).
## Acknowledgements
`Thanks to myanimelist.net API for providing anime data and user ratings.`
This data set contains information on user preference data from 73,516 users on 12,294 anime. Each user is able to add anime to their completed list and give it a rating and this data set is a compilation of those ratings.
## Installation
1. Clone the repository:
```
git clone https://github.com/CodeWithCharan/Anime-Recommender-Streamlit-App.git
```
2. Create a virtual environment (optional): [Virtual Environment Set Up](https://github.com/CodeWithCharan/virtual-env-setup)
3. Install the required dependencies:
```
pip install -r requirements.txt
```
4. Train the model or Download it from: [Google Drive](https://drive.google.com/drive/folders/1Ab_E46FOMCBktotQgeHsUJ5IfIdW27VP?usp=sharing)
5. Run the Streamlit app:
```
streamlit run app.py
```
## Usage
After running the Streamlit app it will open your browser and will go to `http://localhost:####` to use the app. Now, Enter your favorite anime in the search box to get personalized recommendations.