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Tutorials and examples of various recommender systems in industrial applications

License: Apache License 2.0

Python 100.00%

recsys-tutorial-1's Introduction

recsys-tutorial

Tutorials:

implicit: full data & model pipeline, article
LightFM: article
How to build Item2Vec (or W2V) for item recommendations in retail

Classic RecSys:

OK.ru: graph based recsys, article
HH.ru: classic 2 level model of search at hh.ru, article
Okko competition: classic 2 level model, article
Yandex.Dzen: fit ALS -> fit Catboost on warm embeddings to predict warm&cold embeddings, 15-25min in video
TikTok: No use of popularity features! post
Instagram: Insights on candidate generation articles
DoorDash: Store2Vec as a feature in recommendations
Pinterest: Multi-taste user embeddings
AirBnb: Hotel2Vec with novel positive samples approach

Search

How to use W2V and FastText for search: Query2Vec
Avito: FAISS for fast similar embedding search
Similar vectors search with Nmslib (HNSW - hierarchical navigable small world), FAISS (embeddings space K-means clustering + Product quantizer) and Annoy (divides embeddings space with a binary tree)
ElasticSearch basics
DoorDash Elasticsearch meets logistic regression

Upsell

Avito: Recommending additional item - upsell with advanced W2V

Uplift

Directly optimizing Uplift in recsys by change in target

Optimization

Avito Multi-armed bandits for item2item recommendations
RecSys 2018 paper on multi-armed badits for explainable recommendations
Pinterest: Personal notification volume optimization
Uber.Eats: Multi objective optimisation in recsys, article
Avito: Multi-objective optimization in search
VK: Directly optimizing business metrics
GlowByte Consulting: Customer communication chains optimization with RL

Cool articles:

Measure user surprise by serendipidy metric

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