Recommendations with IBM Project

In this project I am dealing with the dataset which will of detail about aticle user interactions. The problem here is I have to give recommendations of articles to users based on articl user interactions. This project satisfies PEP-8 Convention.

Github Link

https://github.com/karthiktsaliki/IBM_Recommendation

Libraries used

• scipy and numpy: SciPy and Numpy are free and open-source Python library used for scientific computing and technical computing.

• pandas: Pandas is a software library written for the Python programming language for data manipulation and analysis.

• matplotlib: Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.

Motivation

Generally, Creating user based recommendations will be helpful because we can show some good content expecting that he has intent to click.

Datasets

user-item-interactions: This data set is actually the table containing which user interacted with which article.

articles_community: This data set consists the details of the articles

Files in repository

This repository contains

• Recommendations_with_IBM.ipynb: Notebook covering all steps to give recommendations
• Recommendations_with_IBM.html: Report of that notebook
• README.md