Course curriculum

  • 1

    Introduction

    • AI Sciences Introduction
    • Instructor Introduction
    • Overview of Recommender Systems
    • Fundamentals of Recommender Systems
    • Project Overview
  • 2

    Motivation for Recommender System

    • Recommender Systems Overview
    • Introduction to Recommender Systems
    • Recommender Systems Process and Goals
    • Generations of Recommender Systems
    • Nexus of AI and Reccommender Systems
    • Applications and Real World Challenges
    • Quiz
    • Quiz Solution
  • 3

    Basic of Recommender System

    • Overview
    • Taxanomy of Recommender Systems
    • ICM
    • User Rating Matrix
    • Quality of Recommender System
    • Online Evaluation Techniques
    • Offline Evaluation Techniques
    • Data Partitioning
    • Important Parameters
    • Error Metric Computation
    • Content Based Filtering
    • Collaborative Filtering and User Based Collaborative Filtering
    • Item Model and Memory Based Collaborative Filtering
    • Quiz
    • Quiz Solution
  • 4

    Machine Learning for Recommender System

    • Overview
    • Benifits of Machine Learning
    • Guidelines for ML
    • Design Approaches for ML
    • Content Based Filtering
    • Data Prepration for Content Based Filtering
    • Data Manipulation for Content Based Filtering
    • Exploring Genres in Content Based Filtering
    • tf-idf Matrix
    • Recommendation Engine
    • Making Recommendations
    • Item Based Collaborative Filtering
    • Item Based Filtering Data Prepration
    • Age Distribution for Users
    • Collaborative Filtering using KNN
    • Geographic Filtering
    • KNN Implementation
    • Making Recommendations with Collaborative Filtering
    • User Based Collaborative Filtering
    • Quiz
    • Quiz Solution
  • 5

    Project 1: Song Recommendation System using content based filtering

    • Project Introduction
    • Dataset Usage
    • Missing Values
    • Exploring Genres
    • Occurence Count
    • tf-idf Implementation
    • Similarity Index
    • Fuzzywuzzy Implementaion
    • Find Closest Title
    • Making Recommendations
  • 6

    Project 2: Movie Recommendation System using collaborative filtering

    • Project Introduction
    • Dataset Discussion
    • Rating Plot
    • Count
    • Logrithm of Count
    • Active Users and Popular Movies
    • Create Collaborative Filter
    • KNN Implementation
    • Making Recommendations