LargeBatchCTR VS openrec

Compare LargeBatchCTR vs openrec and see what are their differences.

LargeBatchCTR

Large batch training of CTR models based on DeepCTR with CowClip. (by bytedance)

openrec

OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms (by ylongqi)
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LargeBatchCTR openrec
1 1
155 406
2.6% -
1.8 0.0
over 1 year ago about 1 year ago
Python Python
Apache License 2.0 Apache License 2.0
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LargeBatchCTR

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

openrec

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

What are some alternatives?

When comparing LargeBatchCTR and openrec you can also consider the following projects:

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.

TensorRec - A TensorFlow recommendation algorithm and framework in Python.

recommenders - Best Practices on Recommendation Systems

compression - Data compression in TensorFlow

pyaes - Pure-Python implementation of AES block-cipher and common modes of operation.

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.

deep-significance - Enabling easy statistical significance testing for deep neural networks.

RecBole - A unified, comprehensive and efficient recommendation library

implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets

torchrec - Pytorch domain library for recommendation systems

deephyper - DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks