| Name | Version | Summary | date |
| qmllib |
1.0.1 |
Python/Fortran toolkit for representation of molecules and solids for machine learning of properties of molecules and solids. |
2024-03-29 20:19:01 |
| python-wgpu-torch-playground |
0.0.1 |
A playground for Python, wgpu, and PyTorch |
2024-03-29 12:12:50 |
| atriumdb |
2.2.3 |
Timeseries Database |
2024-03-28 15:16:17 |
| audinterface |
1.2.1 |
Generic interfaces for signal processing |
2024-03-27 18:52:32 |
| optax |
0.2.2 |
A gradient processing and optimisation library in JAX. |
2024-03-27 18:05:54 |
| nnbench |
0.3.0 |
A small framework for benchmarking machine learning models. |
2024-03-27 15:15:47 |
| intelelm |
1.1.1 |
IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine |
2024-03-27 11:51:12 |
| sapiensqa |
1.0.2 |
SapiensQA (Question and Answer) is a proprietary Machine Learning algorithm for creating Natural Language Processing models where the answers are previously known. |
2024-03-27 07:04:33 |
| sapiensnb |
1.0.4 |
SapiensNB (Naive Bayes) is a classification algorithm that returns a probabilistic result based on Bayes Theorem. |
2024-03-27 06:54:30 |
| sapiensknn |
1.0.3 |
SapiensKNN (K-Nearest Neighbors) is an algorithm for classification and regression that returns the result based on the Euclidean distance between the input values. |
2024-03-27 06:42:28 |
| par-coordinates |
0.2 |
Create parallel coordinates plots of the hyperparameter search |
2024-03-26 18:39:09 |
| fiiireflyyy |
0.1.21 |
A python package covering miscellaneous uses, from system management to machine learning and image or data processing. Developed for personal uses. |
2024-03-26 11:30:40 |
| clinica |
0.8.0 |
Software platform for clinical neuroimaging studies |
2024-03-25 19:30:12 |
| gvision |
1.0.3 |
End-to-end automation platform for computer vision projects. |
2024-03-24 12:10:32 |
| autooc |
0.0.17 |
AutoOC: Automated Machine Learning (AutoML) library for One-Class Learning |
2024-03-24 11:43:38 |
| nvidia-riva-client |
2.15.0 |
Python implementation of the Riva Client API |
2024-03-23 11:26:11 |
| CountEst |
0.1.3 |
CountEst is a module containing the implementation of count-based estimators, i.e., supervised learning algorithms that make predictions based on the frequency or count of specific events, categories, or values within a dataset. |
2024-03-23 10:47:44 |
| ElMTreeIndex |
0.1.10 |
A class for performing knn similarity searches on datasets of chemical formula using the ElMD metric |
2024-03-21 23:15:42 |
| speckcn2 |
0.0.39 |
Estimate Cn2 from Speckle patterns |
2024-03-21 16:37:27 |
| datawaza |
0.1.2 |
Datawaza is a collection of tools for data exploration, visualization, data cleaning, pipeline creation, model iteration, and evaluation. |
2024-03-20 06:52:58 |