https://github.com/jalajthanaki/basic_ecommerce_recomendation_system
This repository contains the code for basic kind of E-commerce recommendation engine. By using the concept of TF-IDF and cosine similarity, we have built this recommendation engine.
https://github.com/jalajthanaki/basic_ecommerce_recomendation_system
cosine-similarity recommendation-system tf-idf-vectorizer
Last synced: 6 months ago
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This repository contains the code for basic kind of E-commerce recommendation engine. By using the concept of TF-IDF and cosine similarity, we have built this recommendation engine.
- Host: GitHub
- URL: https://github.com/jalajthanaki/basic_ecommerce_recomendation_system
- Owner: jalajthanaki
- Created: 2018-03-01T11:45:09.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-03-07T12:56:22.000Z (over 7 years ago)
- Last Synced: 2025-03-23T18:54:21.465Z (7 months ago)
- Topics: cosine-similarity, recommendation-system, tf-idf-vectorizer
- Language: Jupyter Notebook
- Size: 176 KB
- Stars: 30
- Watchers: 1
- Forks: 13
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# E-commerce Recommendation engine
This repository contains the code for basic kind of E-commerce recommendation engine. By using the concept of TF-IDF and cosine similarity, we have built this recommendation engine.
## Data
For this project we are using [this dataset](https://www.kaggle.com/cclark/product-item-data/data). This dataset contains data from the 500 actual SKUs from an outdoor apparel brand's product catalog.
## Dependencies and Installation
We need the following dependencies.
* Pandas: `sudo pip install pandas`
* Sci-kit Learn (sklearn): `sudo pip install -U scikit-learn`
* Jupyter Notebook: `$ sudo pip install jupyter `
## Usage
You need to run the jupyter notebook `Basic_content_based_recommendation_system.ipynb`
## credit
The code of is this repository is inspired by the [Groveco's](https://github.com/groveco/content-engine) content based recommendation engine.