Mastering Multilingual Recommender Systems - Grandmaster Series

Mastering Multilingual Recommender Systems - Grandmaster Series

NVIDIA Developer via YouTube Direct link

– Overview & Summary of the Challenge

2 of 14

2 of 14

– Overview & Summary of the Challenge

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Mastering Multilingual Recommender Systems - Grandmaster Series

Automatically move to the next video in the Classroom when playback concludes

  1. 1 – Introduction
  2. 2 – Overview & Summary of the Challenge
  3. 3 – 2-Stage Recommender Systems Pipeline
  4. 4 – Stage 1 for Tasks 1 & 2: Candidate Generation & Co-Visitation Matrices
  5. 5 – Stage 1: Training Product Embedding
  6. 6 – Stage 2 for Tasks 1 & 2: Pipeline Summary
  7. 7 – Stage 2: Reranker model - Feature Selection & Engineering
  8. 8 – Multilingual Transfer Learning
  9. 9 – Task 3: Next Product Title Generation Solution
  10. 10 – Q&A Session
  11. 11 – Q&A: Challenges of Using Embedding
  12. 12 – Q&A: Unexpected Findings
  13. 13 – Q&A: Critical Model Improvements
  14. 14 – Q&A: Differences from OTTO Multi-Objective RecSys Competition

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.