torchrec VS NVTabular

Compare torchrec vs NVTabular 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)
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torchrec NVTabular
1 1
1,733 1,008
1.6% 0.5%
9.8 5.5
4 days ago 11 days ago
Python Python
BSD 3-clause "New" or "Revised" License Apache License 2.0
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.
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torchrec

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

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.

What are some alternatives?

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

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.

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

federeco - implementation of federated neural collaborative filtering algorithm

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

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

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

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.

FastFold - Optimizing AlphaFold Training and Inference on GPU Clusters

daggy