| Name | Version | Summary | date |
| medaid |
0.1.9 |
Automated Machine Learning for medical use |
2025-01-19 22:53:16 |
| maadstml |
3.52 |
Multi-Agent Accelerator for Data Science (MAADS): Transactional Machine Learning |
2025-01-18 20:43:21 |
| autopocket |
0.11.0 |
Automated Machine Learning project for financial data analysis. |
2025-01-17 14:21:23 |
| atlantic |
1.1.80 |
Atlantic: Automated Preprocessing Framework for Supervised Machine Learning |
2025-01-15 00:08:37 |
| mljar-supervised |
1.1.15 |
Automated Machine Learning for Humans |
2025-01-14 09:08:56 |
| quicktunetool |
0.0.3 |
A Framework for Efficient Model Selection and Hyperparameter Optimization |
2025-01-09 09:50:44 |
| eh-evalml |
0.0.0 |
an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions |
2024-12-23 12:28:30 |
| a2ml |
1.1.0 |
A powerful API to Automate Machine Learning workflows from multiple vendors. |
2024-12-21 03:14:09 |
| perlib |
3.0.7 |
Deep learning, Machine learning and Statistical learning for humans. |
2024-12-19 13:40:54 |
| AutoRAG |
0.3.12 |
Automatically Evaluate RAG pipelines with your own data. Find optimal structure for new RAG product. |
2024-12-09 06:09:23 |
| oracle-automlx |
24.4.1 |
Automated Machine Learning with Explainability |
2024-12-03 09:04:22 |
| dragon-autodl |
1.1 |
Implementation of the algorithmic framework from <An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters> |
2024-12-02 17:46:58 |
| driverlessai |
1.11.1.post1 |
Python client for H2O Driverless AI. |
2024-11-17 18:00:39 |
| evalml-automining |
0.0.2 |
an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions |
2024-11-16 14:31:56 |
| retrain-pipelines |
0.1.1 |
retrain-pipelines lowers the barrier to entry for the creation and management of professional machine learning retraining pipelines. |
2024-11-04 12:35:35 |
| significance_analysis |
0.2.4 |
Significance Analysis for HPO-algorithms performing on multiple benchmarks |
2024-11-01 13:39:32 |
| featrixclient |
2024.1024.1 |
Featrix AI API |
2024-10-24 17:45:18 |
| tsforecasting |
1.4.15 |
TSForecasting: Automated Time Series Forecasting Framework |
2024-10-23 21:06:09 |
| maadsbml |
1.3.19 |
Multi-Agent Accelerator for Data Science (MAADS) Batch AutoML (MAADSBML) |
2024-10-08 01:42:39 |
| significance-analysis |
0.2.1 |
Significance Analysis for HPO-algorithms performing on multiple benchmarks |
2024-09-11 07:05:30 |