Personalised book recommendation system for a user. Similar to goodreads[https://www.goodreads.com/]

Recommender systems provide users with personalised suggestions for product(Books). In this project, we build a book recommender system based on several selected data sets, which estimates the book ratings, age, location, emotion from each user.

The model is predicting user book based recommendations based upon Age, Previous user rating, Location and Emotion. The Emotion are predicted by an LSTM given a sequence of words, determing it's sentimesnt and later on these emotions are used to recommend books to the particular user.

The system uses the algorithms such as collaborative filtering, euclidian distances, K Nearest Neighbourhood, User similarity score and LSTM to predict output emotion for a given sequence of input of words.

The repo name is after [http://nextech.io/index2.html]