Recommendation Systems series for the Waterloo Data Science and Data Engineering meetup

This repository contains the following Jupyter Notebooks.

• Data Visualization for the MovieLens dataset
• Collaboration Filtering Recommenders
• Item Based Collaborative Filtering Recommenders
• User Based Collaborative Filtering Recommenders
• Content-Based Recommenders
• Context-Aware Recommenders

• Azure Notebook / Google Colaboratory
• Python
• Libraries
  • Pandas
  • Numpy
• Machine Learning / Deep Learning
  • scikit-learn
  • Tensorflow
• Dataset used
  • http:https://files.grouplens.org/datasets/movielens/ml-100k.zip (movielens database)
  • https://github.com/sidooms/MovieTweetings (contains dataset of movie tweets, regularly updated)

Introduction to Recommenders Systems presentation is present at https://www.slideshare.net/ZiaBabar/introduction-to-recommendation-systems-87809727