Becoming an expert in ML, NLP, data story telling and encouraging others to do the same. Sr Data Scientist, Toronto Canada. https://www.linkedin.com/in/susanli/
I have added a few lines of code. Thanks for reminder.
This tutorial may be help: https://www.machinelearningplus.com/nlp/topic-modeling-python-sklearn-examples/
Good catch. My next article will be LDA + document similarity = rec system.
Thanks for letting me know. I have updated.
I am preparing an article: LDA + document similarity + content-based recommender system. It will cover these.
Sklearn and Gensim both have topic modeling(LDA), try which one fits your needs.
Check out this tutorial: https://www.machinelearningplus.com/nlp/topic-modeling-gensim-python/
This means you did not define X_mat earlier.
You need to convert pandas dataframe to surprise dataframe and yes, surprise dataframe must have three columns, user ids, item ids, and ratings in this order.
When you need to load it:
model = open(‘model.pkl’,’rb’)
model = joblib.load(model)