| rhiever/Data-Analysis-and-Machine-Learning-Projects |
5,596 |
|
0 |
0 |
almost 3 years ago |
0 |
|
12 |
|
Jupyter Notebook |
| Repository of teaching materials, code, and data for my data analysis and machine learning projects. |
| rh12503/triangula |
3,832 |
|
0 |
0 |
over 4 years ago |
57 |
September 16, 2021 |
|
mit |
Go |
| Generate high-quality triangulated and polygonal art from images. |
| geatpy-dev/geatpy |
1,633 |
|
0 |
0 |
about 3 years ago |
0 |
|
98 |
lgpl-3.0 |
Python |
| Evolutionary algorithm toolbox and framework with high performance for Python |
| MilesCranmer/PySR |
1,580 |
|
0 |
0 |
about 2 years ago |
165 |
August 21, 2023 |
76 |
apache-2.0 |
Python |
| High-Performance Symbolic Regression in Python and Julia |
| ahmedfgad/GeneticAlgorithmPython |
1,564 |
|
0 |
8 |
over 2 years ago |
57 |
September 08, 2023 |
77 |
bsd-3-clause |
Python |
| Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch). |
| BIMK/PlatEMO |
1,292 |
|
0 |
0 |
over 2 years ago |
0 |
|
66 |
|
MATLAB |
| Evolutionary multi-objective optimization platform |
| MorvanZhou/Evolutionary-Algorithm |
1,152 |
|
0 |
0 |
over 2 years ago |
0 |
|
4 |
mit |
Python |
| Evolutionary Algorithm using Python, 莫烦Python 中文AI教学 |
| google/vizier |
1,142 |
|
0 |
3 |
about 2 years ago |
35 |
November 30, 2023 |
44 |
apache-2.0 |
Python |
| Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service. |
| facebookexperimental/Robyn |
974 |
|
0 |
0 |
about 2 years ago |
3 |
February 08, 2023 |
67 |
mit |
Jupyter Notebook |
| Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community. |
| ArztSamuel/Applying_EANNs |
955 |
|
0 |
0 |
over 8 years ago |
0 |
|
0 |
mit |
ASP |
| A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm. |
