| Name | Version | Summary | date |
| hyperparameter-tuning |
0.3.1 |
A minimal framework for running hyperparameter tuning |
2023-09-05 09:38:53 |
| qaekwy |
0.1.4 |
Python Client library for Qaekwy Operational Research Solver |
2023-09-02 12:33:19 |
| optrs |
0.1.1 |
Molecular molecule optimization with forcefields |
2023-08-28 20:28:08 |
| clean-df |
0.3.0 |
Python module to report, clean, and optimize Pandas Dataframes effectively |
2023-08-22 21:24:59 |
| unused-attributes |
0.1.10 |
Find class unused attributes |
2023-08-08 19:57:47 |
| scrilla |
1.6.0 |
a financial optimization program |
2023-07-31 13:41:25 |
| ttopt |
0.6.2 |
Multivariate function optimizer based on the tensor train approach. |
2023-07-27 20:14:25 |
| chess-tuning-tools |
0.9.5 |
A collection of tools for local and distributed tuning of chess engines. |
2023-07-19 15:49:09 |
| bask |
0.10.9 |
A fully Bayesian implementation of sequential model-based optimization |
2023-07-19 14:39:14 |
| ExperimentsPyDesign |
0.1.0 |
Experimental Designs in Python with additional tooling |
2023-07-18 03:07:41 |
| deduplicationdict |
1.0.4 |
A dictionary that de-duplicates values. |
2023-07-03 03:30:12 |
| knarrow |
0.8.0 |
Shoot a knarrow to the knee |
2023-07-01 17:11:12 |
| rtc-tools-hydraulic-structures |
2.0.0a15 |
Hydraulic structures models for RTC-Tools 2. |
2023-06-30 15:10:20 |
| EDAspy |
1.1.1 |
EDAspy is a Python package that implements Estimation of Distribution Algorithms. EDAspy allows toeither use already existing implementations or customize the EDAs baseline easily building it bymodules so new research can be easily developed. It also has several benchmarks for comparisons. |
2023-06-28 09:36:34 |
| optimazing |
0.1.0 |
Wrapper around scipy.optimize.minimize |
2023-06-27 15:49:47 |
| autograd |
1.6.2 |
Efficiently computes derivatives of numpy code. |
2023-06-23 08:36:41 |
| leggedsnake |
0.4.0 |
Simulate and optimize planar leg mechanisms using PSO and GA |
2023-06-21 08:02:12 |
| LinearProgramOptimizer |
1.0.2 |
Optimization models for solving Linear Programming Problems |
2023-06-19 07:16:19 |
| torch-dreams |
4.0.0 |
Making neural networks more interpretable, for research and art |
2023-06-14 08:24:19 |
| coexist |
0.3.2 |
Learning simulation parameters from experimental data, from the micro to the macro, from the laptop to the cluster. |
2023-06-11 02:52:57 |