RecSys 2020 Tutorial: Feature Engineering for Recommender Systems

Feature Engineering for Recommender Systems by Benedikt Schifferer (Nvidia), Chris Deotte (Nvidia) and Even Oldridge (Nvidia) The selection of features and proper preparation of data for deep learning or machine learning models plays a significant role in the performance of recommender systems. To address this we propose a tutorial highlighting best practices and optimization techniques for feature engineering and preprocessing of recommender system datasets. The tutorial will explore feature engineering using pandas and Dask, and will also cover acceleration on the GPU using open source libraries like RAPIDS cuDF and NVTabular.

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RecSys 2020 Tutorial: Introduction to Bandits in Recommender Systems
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RecSys 2020 Tutorial: Introduction to Bandits in Recommender Systems

Algo Hour - Behavioral Testing of Recommender Systems with RecList | Jacopo Tagliabue, Coveo
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Algo Hour - Behavioral Testing of Recommender Systems with RecList | Jacopo Tagliabue, Coveo

Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon
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Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon

Real-Time Search and Recommendation at Scale Using Embeddings and Hopsworks
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Real-Time Search and Recommendation at Scale Using Embeddings and Hopsworks

Youtube Discovery Evolution by Lukasz Heldt | VideoRecSys Workshop Keynote | RecSys 2023
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Youtube Discovery Evolution by Lukasz Heldt | VideoRecSys Workshop Keynote | RecSys 2023

KDD 2020: Hands-onTutorials: Deep Learning for Search and Recommender Systems in Practice-Part 1
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KDD 2020: Hands-onTutorials: Deep Learning for Search and Recommender Systems in Practice-Part 1

Building Production Recommender Systems - Maciej Kula - WEB2DAY 2017
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Building Production Recommender Systems - Maciej Kula - WEB2DAY 2017

Mastering Recommender Systems | Grandmaster Series E8
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Mastering Recommender Systems | Grandmaster Series E8

Wayfair Data Science Explains It All: Evaluating Recommender Systems
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Wayfair Data Science Explains It All: Evaluating Recommender Systems

Mastering Multilingual Recommender Systems | Grandmaster Series E9
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Mastering Multilingual Recommender Systems | Grandmaster Series E9

8 Recommender Systems - Machine Learning Class 10-701
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8 Recommender Systems - Machine Learning Class 10-701

Maciej Kula | Neural Networks for Recommender Systems
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Maciej Kula | Neural Networks for Recommender Systems

RecSys 2016: Tutorial on Lessons Learned from Building Real-life Recommender Systems
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RecSys 2016: Tutorial on Lessons Learned from Building Real-life Recommender Systems

How does Netflix recommend movies? Matrix Factorization
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How does Netflix recommend movies? Matrix Factorization

Maciej Arciuch, Karol Grzegorczyk: Embeddings! Embeddings everywhere! | PyData London 2019
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Maciej Arciuch, Karol Grzegorczyk: Embeddings! Embeddings everywhere! | PyData London 2019

Machine Learning Course - 23. ML Design Pattern - Ranking
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Machine Learning Course - 23. ML Design Pattern - Ranking

"Reinforcement Learning for Recommender Systems: A Case Study on Youtube," by Minmin Chen
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"Reinforcement Learning for Recommender Systems: A Case Study on Youtube," by Minmin Chen

Introduction to Feature Engineering in Machine Learning
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Introduction to Feature Engineering in Machine Learning

Recommender Systems using Graph Neural Networks
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Recommender Systems using Graph Neural Networks

Deep Learning for Recommender Systems (Nick Pentreath)
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Deep Learning for Recommender Systems (Nick Pentreath)