The main goal of this project is to recommend the 5 movies based on user interest.

• Demo
• Problem Statement
• Approach
• Technologies Used
• Installation
• Deployement on Heroku
• Detailed Project Reports
• Bugs & Logs
• Contributors

Link: https://moviesrecommenders.herokuapp.com/

Dog Breed Identification Determine the breed of a dog in an image In today’s technology driven world, recommender systems are socially and economically critical for ensuring that individuals can make appropriate choices surrounding the content they engage with on a daily basis. One application where this is especially true surrounds movie content recommendations; where intelligent algorithms can help viewers find great titles from tens of thousands of options.

Providing an accurate and robust solution to this challenge has immense economic potential, with users of the system being exposed to content they would like to view or purchase - generating revenue and platform affinity.

Data Exploration : I started exploring dataset using pandas,numpy,matplotlib and seaborn.

Feature Engineering : Removed missing values and created new features as per insights.

Pickle File : created pickle file as per need.

User Interface & deployment : Created an UI with a form that take the necessary inputs from user and shows the 5 recommended movies. After that I have deployed project on heroku.

1. Python
2. Streamlit
3. Sklearn(CountVectorizer, cosine_similarity)
4. Pandas, Numpy

Download here

Click here to install python. To install the required packages and libraries, run this pip command in the project directory after cloning the repository:

git clone https://github.com/hrishikeshkini/movie-recommender-system.git
pip install -r requirements.txt

If pip is not already installed, Follow this link

Create a virtual app on Heroku Cloud. You can either connect your github profile or download cli to manually deploy this project. Follow the instruction given on Heroku Documentation to deploy a web app.

1. If you find a bug, kindly open an issue and it will be addressed as early as possible. Open
2. Under localhost, logging is performed for all the actions and its stored onto logs.txt file
3. When the app is deployed on heroku, logs can be viewed on heroku dashboard or CLI.

Hrishikesh Kini