| 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). |
| PaddlePaddle/Quantum |
456 |
|
0 |
0 |
almost 3 years ago |
13 |
May 19, 2022 |
21 |
other |
Jupyter Notebook |
| noahgift/functional_intro_to_python |
239 |
|
0 |
0 |
almost 5 years ago |
0 |
|
14 |
other |
Jupyter Notebook |
| [tutorial]A functional, Data Science focused introduction to Python |
| mmckerns/tutmom |
236 |
|
0 |
0 |
about 3 years ago |
0 |
|
1 |
bsd-3-clause |
Jupyter Notebook |
| Tutorial on "Modern Optimization Methods in Python" |
| ankonzoid/LearningX |
213 |
|
0 |
0 |
over 5 years ago |
0 |
|
3 |
mit |
Python |
| Deep & Classical Reinforcement Learning + Machine Learning Examples in Python |
| ahmedfgad/NeuralGenetic |
201 |
|
0 |
0 |
almost 3 years ago |
0 |
|
2 |
|
Python |
| Building and training artificial neural networks (regression or classification) using the genetic algorithm. |
| secondmind-labs/trieste |
196 |
|
0 |
1 |
about 2 years ago |
30 |
December 19, 2023 |
60 |
apache-2.0 |
Python |
| A Bayesian optimization toolbox built on TensorFlow |
| jump-dev/JuMPTutorials.jl |
138 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| Tutorials on using JuMP for mathematical optimization in Julia |
| jlblancoc/tutorial-se3-manifold |
134 |
|
0 |
0 |
almost 4 years ago |
0 |
|
3 |
|
TeX |
| LaTeX sources of the technical report "A tutorial on SE(3) transformation parameterizations and on-manifold optimization" |
| carloluis/webpack-demo |
131 |
|
0 |
0 |
over 4 years ago |
0 |
|
17 |
mit |
JavaScript |
| webpack 4 config. demo :gear: |
