Buffalo
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| D2l En | 18,049 | 2 days ago | 101 | other | Python | |||||
| Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge. | ||||||||||
| Recommenders | 15,810 |  | 2 | 9 hours ago | 11 | April 01, 2022 | 166 | mit | Python | |
| Best Practices on Recommendation Systems | ||||||||||
| Qdrant | 10,889 | 4 hours ago | 94 | apache-2.0 | Rust | |||||
| Qdrant - Vector Database for the next generation of AI applications. Also available in the cloud https://cloud.qdrant.io/ | ||||||||||
| Gorse | 6,897 | 1 | 2 days ago | 46 | September 13, 2022 | 42 | apache-2.0 | Go | ||
| Gorse open source recommender system engine | ||||||||||
| Deep Learning Interview Book | 5,149 | 4 months ago | 9 | |||||||
| 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） | ||||||||||
| Lightfm | 4,338 |  | 28 | 17 | 18 days ago | 14 | November 27, 2020 | 142 | apache-2.0 | Python |
| A Python implementation of LightFM, a hybrid recommendation algorithm. | ||||||||||
| Alink | 3,343 | 1 | 2 months ago | 16 | September 08, 2022 | 48 | apache-2.0 | Java | ||
| Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform. | ||||||||||
| Implicit | 3,173 |  | 22 | 10 | a day ago | 43 | January 29, 2022 | 80 | mit | Python |
| Fast Python Collaborative Filtering for Implicit Feedback Datasets | ||||||||||
| Catalyst | 3,106 |  | 19 | 10 | 2 months ago | 108 | April 29, 2022 | 5 | apache-2.0 | Python |
| Accelerated deep learning R&D | ||||||||||
| Ad Papers | 3,009 | 2 years ago | 2 | mit | Python | |||||
| Papers on Computational Advertising | ||||||||||
Buffalo
Buffalo is a fast and scalable production-ready open source project for recommender systems. Buffalo effectively utilizes system resources, enabling high performance even on low-spec machines. The implementation is optimized for CPU and SSD. Even so, it shows good performance with GPU accelerator, too. Buffalo, developed by Kakao, has been reliably used in production for various Kakao services.
For more information see the documentation
Requirements
- Python 3.8+
- cmake 3.17+
- gcc/g++ (with std=c++14)
License
This software is licensed under the Apache 2 license, quoted below.
Copyright 2020 Kakao Corp. http://www.kakaocorp.com
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this project except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
