├── README.md
└── .gitignore


/README.md:
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 1 | # E-commerce Recommendation engine
 2 | 
 3 | 
 4 | 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.
 5 | 
 6 | ## Data
 7 | 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. 
 8 | 
 9 | ## Dependencies and Installation 
10 | We need the following dependencies.
11 | 
12 | * Pandas: `sudo pip install pandas`
13 | * Sci-kit Learn (sklearn): `sudo pip install -U scikit-learn`
14 | * Jupyter Notebook: `$ sudo pip install jupyter `
15 | 
16 | ## Usage
17 | You need to run the jupyter notebook `Basic_content_based_recommendation_system.ipynb`
18 | 
19 | ## credit
20 | The code of is this repository is inspired by the [Groveco's](https://github.com/groveco/content-engine) content based recommendation engine.


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