| ScottfreeLLC/AlphaPy |
1,003 |
|
0 |
0 |
over 2 years ago |
25 |
August 29, 2020 |
13 |
apache-2.0 |
Python |
| Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost |
| kyleskom/NBA-Machine-Learning-Sports-Betting |
904 |
|
0 |
0 |
over 2 years ago |
0 |
|
8 |
|
Python |
| NBA sports betting using machine learning |
| chonyy/ML-auto-baseball-pitching-overlay |
219 |
|
0 |
0 |
over 4 years ago |
0 |
|
2 |
|
Python |
| ⚾🤖⚾ Automatic baseball pitching overlay in realtime |
| ChenFengYe/SportsCap |
139 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
|
Python |
| [IJCV 2021] SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos |
| Furkan-Gulsen/Sport-With-AI |
107 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
apache-2.0 |
Jupyter Notebook |
| The human body is detected with the help of the Mediapipe library. Then, using the mathematical methods applied, it is determined how much the exercise count is done. |
| rdroste/unisal |
70 |
|
0 |
0 |
almost 5 years ago |
0 |
|
1 |
apache-2.0 |
Python |
| Unified Image and Video Saliency Modeling (ECCV 2020) |
| chychen/BasketballGAN |
48 |
|
0 |
0 |
about 3 years ago |
0 |
|
3 |
|
Python |
| Basketball coaches often sketch plays on a whiteboard to help players get the ball through the net. A new AI model predicts how opponents would respond to these tactics. |
| TianHongTao/ID-DAML |
43 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
|
Python |
| 推荐系统---实验+复现+创新 |
| eborboihuc/Deep360Pilot-CVPR17 |
32 |
|
0 |
0 |
over 8 years ago |
0 |
|
2 |
|
Python |
| Official Implementation of CVPR 2017 Oral paper "Deep 360 Pilot: Learning a Deep Agent for Piloting through 360◦ Sports Videos" |
| lood339/SCCvSD |
32 |
|
0 |
0 |
about 5 years ago |
0 |
|
3 |
bsd-2-clause |
Python |
| Sports Camera Calibration via Synthesic Data |
