https://github.com/abu14/movie_recommendation_system

Content Based Recommendation System for users similar to the movie a user liked and analyses the sentiments on the reviews given by other users for that movie and otehers.
https://github.com/abu14/movie_recommendation_system

mahinelearning pandas python recommendation-engine recommendation-system sklearn

Last synced: 3 months ago
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Content Based Recommendation System for users similar to the movie a user liked and analyses the sentiments on the reviews given by other users for that movie and otehers.

• Host: GitHub
• URL: https://github.com/abu14/movie_recommendation_system
• Owner: abu14
• Created: 2025-01-14T17:59:22.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2025-01-14T19:44:41.000Z (5 months ago)
• Last Synced: 2025-03-15T07:17:30.800Z (3 months ago)
• Topics: mahinelearning, pandas, python, recommendation-engine, recommendation-system, sklearn
• Language: Jupyter Notebook
• Homepage:
• Size: 3.14 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Hi, I'm Abenezer Tesfaye! 👋

## 🚀 About Me

I'm a Machine Learning Engineer / Data Analyst

Currently working as a Data Analytics Developer.

# **I built a Movie Recommender System**

Content Based Recommender System recommends movies similar to the movie user likes and analyses the sentiments on the reviews given by the user for that movie.

The details of the movies(title, genre, runtime, rating, poster, etc) are fetched using an API by TMDB, https://www.themoviedb.org/documentation/api, and using the IMDB id of the movie in the API. 

I used *web scraping* to get the reviews given by the user in the IMDB site using beautifulsoup4 and performed sentiment analysis on those reviews.

## Deployment

### Steps To Deploy The App:

I Prepared the dataset:

        1. Data Extraction

        2. Exploratory Data Analysis(EDA)

        3. Feature Engineering

        4. Model Building and Tuning

        5. Building Flask API

        6. Pushing code to Github

        7. Connecting to a Heroku account 

        8. Deploy App

![logo](https://github.com/MrBriit/Netflix-Recommender-System-and-Deployment/blob/main/net%20screenshot.png?raw=true)

## 🔗 Links

[![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/abenezer-tesfaye-191579214/)

## 🛠 Skills

- Python  

- Statistics 

- SQL 

- Machine Learning 

- Deep Learning

- Artificial Intelligence

- Data Analytics