ankishb / Recommender-System

This is highly involved project on recommendation system with classical and advance method.

Recommender-System

This is highly involved project on recommendation system with classical and advance method.

Project timeline

1. At Ist stage, we will discuss basics of recommender system and run algorithms on Movie Lens Dataset. Time period of this notebook will be 5 days
2. At second stage we will extend the same idea to text based recommendation system where we will explore feature extraction for text such as tf-idf, word-embedding, sent2vec etc. This will be a heavy deep learning based system. It will be of 7 days time period.
3. At third stage, we will explore some of the practical aspect of recommender system such as evaluation metrics, cross-validation etc. Then we will make a hybrid system. This type of models are used in real world application such as netflix, instagram, facebook, amazon etc. It won't be of the same level , but it will provide their essence at brief. It will take around 2 weeks.
4. At final stage, we will exploregraph neural network for this domain. We will run experiments on building a good and advance features for recommender system. Time period for this stage will be decided later.