Best Practices on Recommendation Systems
-
Updated
Nov 1, 2024 - Python
Best Practices on Recommendation Systems
深度学习面试宝典(含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向)
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
Fast Python Collaborative Filtering for Implicit Feedback Datasets
A unified, comprehensive and efficient recommendation library
计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估
Pytorch domain library for recommendation systems
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
A TensorFlow recommendation algorithm and framework in Python.
An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.
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.
推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction
AI-related tutorials. Access any of them for free → https://towardsai.net/editorial
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
A Comparative Framework for Multimodal Recommender Systems
深度学习在推荐系统中的应用及论文小结。
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
Add a description, image, and links to the recommendation-system topic page so that developers can more easily learn about it.
To associate your repository with the recommendation-system topic, visit your repo's landing page and select "manage topics."