NVTabular VS torchrec

Compare NVTabular vs torchrec and see what are their differences.

NVTabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems. (by NVIDIA-Merlin)
Deep Learning feature-engineering feature-selection GPU Machine Learning Nvidia preprocessing recommendation-system recommender-system
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torchrec

Pytorch domain library for recommendation systems (by pytorch)
Pytorch GPU Deep Learning Cuda recommender-system recommendation-system Sharding
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NVTabular torchrec
1 1
1,006 1,723
1.2% 3.6%
5.5 9.7
4 days ago 7 days ago
Python Python
Apache License 2.0 BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

NVTabular

Posts with mentions or reviews of NVTabular. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-08.

torchrec

Posts with mentions or reviews of torchrec. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing NVTabular and torchrec you can also consider the following projects:

dbt-expectations - Port(ish) of Great Expectations to dbt test macros

Federated-Recommendation-Neural-Collaborative-Filtering - Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system.

Scio - A Scala API for Apache Beam and Google Cloud Dataflow.

warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

cuetils - CLI and library for diff, patch, and ETL operations on CUE, JSON, and Yaml

federeco - implementation of federated neural collaborative filtering algorithm

cascade - Lightweight and modular MLOps library targeted at small teams or individuals

LLMRec - [WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"

NewsMTSC - Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.

daggy

FastFold - Optimizing AlphaFold Training and Inference on GPU Clusters

NVTabular vs dbt-expectations torchrec vs Federated-Recommendation-Neural-Collaborative-Filtering NVTabular vs Scio torchrec vs warp-drive NVTabular vs cuetils torchrec vs federeco NVTabular vs cascade torchrec vs LLMRec NVTabular vs federeco torchrec vs NewsMTSC NVTabular vs daggy torchrec vs FastFold