Building Robust and Scalable Recommendation Engines for Online Food Delivery

Explore the intricacies of building robust and scalable recommendation engines for online food delivery in this 25-minute training session. Discover how to leverage the Delivery Hero Recommendation Dataset (DHRD) through data collection, preprocessing, and feature engineering techniques. Learn to create personalized recommendations catering to diverse customer tastes and dietary preferences. Gain insights into handling large-scale datasets and implementing scalable algorithms like matrix factorization and ensemble methods. Dive into the data science workflow, including exploratory data analysis, model selection, evaluation metrics, and business metrics. Understand the architecture behind successful recommendation systems and how to apply these concepts to the food delivery industry.

- Introductions
- Recommendation Systems
- Overview of DS Workflow
- EDA
- Models
- Evaluation Metrics
- Business Metrics
- Architecture
- DHRD