| beta-team/beta-recsys |
152 |
|
0 |
0 |
over 2 years ago |
6 |
February 28, 2021 |
20 |
mit |
Python |
| Beta-RecSys: Build, Evaluate and Tune Automated Recommender Systems |
| jremmons/AWSLambdaFace |
96 |
|
0 |
0 |
almost 8 years ago |
0 |
|
3 |
gpl-3.0 |
Python |
| Perform deep neural network based face detection and recognition in the cloud (via AWS lambda) with zero model configuration or tuning. |
| KordingLab/spykes |
68 |
|
0 |
0 |
about 6 years ago |
5 |
November 14, 2017 |
9 |
mit |
Python |
| Tools for spike data analysis and visualization |
| adiyoss/WatermarkNN |
32 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
mit |
Python |
| Watermarking Deep Neural Networks (USENIX 2018) |
| Oneplus/segrep-for-nn-semicrf |
31 |
|
0 |
0 |
about 9 years ago |
0 |
|
1 |
|
C++ |
| Code for Exploring Segment Representations for Neural Segmentation Models |
| countif/enas_nni |
25 |
|
0 |
0 |
about 7 years ago |
0 |
|
5 |
|
Python |
| This code is for running enas on nni. |
| IEEE-NITK/Neural-Voice-Cloning |
23 |
|
0 |
0 |
about 7 years ago |
0 |
|
2 |
|
Jupyter Notebook |
| Neural Voice Cloning with a few voice samples, using the speaker adaptation method. Speaker adaptation is based on fine-tuning a multi-speaker generative model with a few cloning samples. |
| WilsonWangTHU/neural_graph_evolution |
22 |
|
0 |
0 |
about 6 years ago |
0 |
|
2 |
mit |
Python |
| dangnam739/deep-learning-coursera |
16 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| DantrazTrev/Neural-Networks |
10 |
|
0 |
0 |
almost 4 years ago |
0 |
|
13 |
|
Python |
| A basic ANN repository for understanding Neural networks without any black box approach |
