Recommendation Systems Development

What You Will Learn

• 1 Learn the fundamentals of recommendation systems and their business impact.
• 2 Understand data collection strategies and preprocessing for recommendation pipelines.
• 3 Apply content-based filtering using item features and user profiles.
• 4 Implement collaborative filtering with user-item interactions.
• 5 Explore matrix factorization and embedding techniques for latent factors.
• 6 Build deep learning models for sequential and context-aware recommendations.
• 7 Evaluate system performance using offline metrics and online A/B testing.
• 8 Design scalable real-time recommendation architectures.
• 9 Create hybrid models combining multiple recommendation strategies.
• 10 Deploy, monitor, and ensure fairness and transparency in recommendation systems.