| qdrant/qdrant |
15,789 |
|
0 |
0 |
about 2 years ago |
0 |
|
212 |
apache-2.0 |
Rust |
| Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/ |
| hora-search/hora |
2,469 |
|
0 |
0 |
over 2 years ago |
2 |
August 07, 2021 |
23 |
apache-2.0 |
Rust |
| 🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 . |
| robi56/Deep-Learning-for-Recommendation-Systems |
2,141 |
|
0 |
0 |
about 6 years ago |
0 |
|
0 |
|
|
| This repository contains Deep Learning based articles , paper and repositories for Recommender Systems |
| greyhatguy007/Machine-Learning-Specialization-Coursera |
2,082 |
|
0 |
0 |
over 2 years ago |
0 |
|
16 |
mit |
Jupyter Notebook |
| Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG |
| ZiyaoGeng/RecLearn |
1,406 |
|
0 |
0 |
almost 4 years ago |
0 |
|
5 |
mit |
Python |
| Recommender Learning with Tensorflow2.x |
| m2dsupsdlclass/lectures-labs |
1,309 |
|
0 |
0 |
over 3 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris |
| cheungdaven/DeepRec |
1,068 |
|
0 |
0 |
almost 4 years ago |
0 |
|
8 |
gpl-3.0 |
Python |
| An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow. |
| MaurizioFD/RecSys2019_DeepLearning_Evaluation |
871 |
|
0 |
0 |
about 4 years ago |
0 |
|
1 |
agpl-3.0 |
Python |
| 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. |
| wubinzzu/NeuRec |
861 |
|
0 |
0 |
over 4 years ago |
1 |
November 04, 2019 |
15 |
|
Python |
| Next RecSys Library |
| towardsai/tutorials |
847 |
|
0 |
0 |
over 3 years ago |
0 |
|
3 |
other |
Jupyter Notebook |
| AI-related tutorials. Access any of them for free → https://towardsai.net/editorial |