Skip to main content
Learn AI Create the Future — with Pranay
  • Learn
  • Paths
  • Projects
  • Practice
  • Glossary
  • Errors
  • LeetCode
  • Main site

Main site →
Select language

Translation is unavailable right now. Your browser’s own “Translate page” usually works.

Machine translation by Google

Topics

  • 🧱 Foundations 2 sections
  • 🤖 Machine Learning 11 sections
  • 📊 Statistics and Experiments 4 sections
  • 🧭 Doing the Work 9 sections
  • 🧠 Deep Learning 11 sections
  • 🧰 Libraries and Frameworks 4 sections
  • 💬 Language and NLP 15 sections
  • 👁️ Computer Vision 13 sections
  • 🎙️ Speech, Forecasting and Recommenders 3 sections
    • Speech and Audio AI 12 lessons
    • Time Series and Forecasting 12 lessons
    • Recommender Systems 12 lessons
      • Overview
      • What is a recommender system?
      • Collaborative filtering
      • Content-based filtering
      • Matrix factorisation
      • Implicit feedback
      • The cold-start problem
      • Hybrid recommenders
      • Ranking metrics
      • Two-tower retrieval models
      • Sequence-aware recommendation
      • Diversity and filter bubbles
      • A/B testing a recommender
  • ✨ Generative AI and LLMs 4 sections
  • 🔬 Inside a Transformer 11 sections
  • ⚙️ Production and MLOps 16 sections
  • 🌍 AI in the Real World 12 sections
  • ⚖️ Safety, Ethics and Law 2 sections

See all topics

  1. Home
  2. Learn
  3. Recommender Systems

🎙️ Speech, Forecasting and Recommenders · Section 071

🎯 Recommender Systems

How YouTube, Netflix and Amazon decide what to show you next.

Every lesson in this section is written by Pranay Mahendrakar.

12 of 12 lessons published · Three reading levels on every lesson

Start with “What is a recommender system?”

Lessons in order

Work top to bottom. Each lesson assumes the one above it.

  1. 01 What is a recommender system?
  2. 02 Collaborative filtering
  3. 03 Content-based filtering
  4. 04 Matrix factorisation
  5. 05 Implicit feedback
  6. 06 The cold-start problem
  7. 07 Hybrid recommenders
  8. 08 Ranking metrics
  9. 09 Two-tower retrieval models
  10. 10 Sequence-aware recommendation
  11. 11 Diversity and filter bubbles
  12. 12 A/B testing a recommender
Previous Time Series and Forecasting Next Generative AI

Learn AI

Learn Artificial Intelligence the easy way.

Learn. Build. Ask. Share.

Free forever. No sign-up, no ads, no tracking.

Learn

  • All topics
  • Learning paths
  • Projects
  • Practice playground
  • AI glossary
  • Error database
  • LeetCode solutions

Start here

  • Python for AI
  • Mathematics for AI
  • Machine Learning
  • Classic Algorithms in Depth
  • Linear Models and Regularisation
  • Ensembles and Gradient Boosting

This site

  • Search
  • New lessons feed
  • Sitemap
  • About Pranay Mahendrakar
  • pranaymahendrakar.com

© 2026 Pranay Mahendrakar. Written for people who are starting from zero.

10 new lessons every day. If something here is wrong or confusing, that is worth fixing — say so.