| Name | Version | Summary | date |
| pixeltable |
0.3.2 |
AI Data Infrastructure: Declarative, Multimodal, and Incremental |
2025-01-31 22:13:14 |
| sysidentpy |
0.5.1 |
A Python Package For System Identification Using NARMAX Models |
2025-01-29 02:03:19 |
| data-science-utils |
1.8.1 |
Data Science Utils extends the Scikit-Learn API and Matplotlib API to provide simple methods that simplify tasks and visualizations for data science projects. |
2025-01-28 19:31:41 |
| sb3-contrib |
2.5.0 |
Contrib package of Stable Baselines3, experimental code. |
2025-01-27 12:11:09 |
| skpro |
2.9.0 |
A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python |
2025-01-26 01:51:53 |
| syd |
0.1.6 |
A Python package for making GUIs for data science easy. |
2025-01-22 21:00:46 |
| argilla-server |
2.7.0 |
Open-source tool for exploring, labeling, and monitoring data for NLP projects. |
2025-01-21 13:35:58 |
| ydata-profiling |
4.12.2 |
Generate profile report for pandas DataFrame |
2025-01-20 16:42:41 |
| tsml |
0.6.1 |
A development sandbox for time series machine learning algorithms. |
2025-01-11 21:30:00 |
| span-marker |
1.7.0 |
Named Entity Recognition using Span Markers |
2025-01-08 11:39:11 |
| stable-baselines3 |
2.4.1 |
Pytorch version of Stable Baselines, implementations of reinforcement learning algorithms. |
2025-01-07 13:22:42 |
| future-sales-prediction-2024 |
3.4.17 |
A package for feature extraction, hyperopt, and validation schemas |
2024-12-23 13:08:33 |
| statmoments |
1.1.0 |
Fast streaming single-pass univariate/bivariate statistics and t-test |
2024-12-22 07:18:18 |
| pymandala |
0.2.0a0 |
A powerful and easy to use experiment tracking framework |
2024-12-20 21:13:03 |
| scanscope |
1.0.0 |
Visualize portscan results |
2024-12-20 13:01:05 |
| skchange |
0.10.0 |
Sktime-compatible change and anomaly detection |
2024-12-13 08:03:29 |
| aeon |
1.0.0 |
A toolkit for machine learning from time series |
2024-11-28 17:25:52 |
| netmedpy |
0.1.4 |
NetMedPy evaluates network localization (statistical analysis of the largest connected component/subgraph or LCC), calculates proximity and separation between biological entities, and conducts screenings involving a large number of diseases and drug targets. |
2024-11-25 23:07:37 |
| ds-future-sales-2024 |
0.1.2 |
A package for feature extraction, hyperopt, and validation schemas |
2024-11-22 09:38:36 |
| rl-zoo3 |
2.4.0 |
A Training Framework for Stable Baselines3 Reinforcement Learning Agents |
2024-11-18 10:32:36 |