VBAF

4.0.0

VBAF (Visual Business Automation Framework) - A complete Deep Q-Network (DQN) reinforcement learning framework built entirely in PowerShell 5.1. No Python. No dependencies. 27 phases: Core DQN engine, Q-Learning, Neural Networks, and 14 enterprise automation pillars including SelfHealing, AnomalyDetector, IncidentResponder, ComplianceReporter, UserBehaviorAnalytics, P
VBAF (Visual Business Automation Framework) - A complete Deep Q-Network (DQN) reinforcement learning framework built entirely in PowerShell 5.1. No Python. No dependencies. 27 phases: Core DQN engine, Q-Learning, Neural Networks, and 14 enterprise automation pillars including SelfHealing, AnomalyDetector, IncidentResponder, ComplianceReporter, UserBehaviorAnalytics, PatchIntelligence, BackupOptimizer, EnergyOptimizer, MultiSiteCoordinator, and AutoPilot (crown jewel � one agent orchestrating all 13 pillars). Real Windows data: WMI, Get-WinEvent, Get-Service, Get-HotFix. GitHub: https://github.com/JupyterPS/VBAF
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Minimum PowerShell version

5.1

Installation Options

Copy and Paste the following command to install this package using PowerShellGet More Info

Install-Module -Name VBAF

Copy and Paste the following command to install this package using Microsoft.PowerShell.PSResourceGet More Info

Install-PSResource -Name VBAF

You can deploy this package directly to Azure Automation. Note that deploying packages with dependencies will deploy all the dependencies to Azure Automation. Learn More

Manually download the .nupkg file to your system's default download location. Note that the file won't be unpacked, and won't include any dependencies. Learn More

Owners

Copyright

(c) 2025-2026 Henning. All rights reserved.

Package Details

Author(s)

  • Henning

Tags

AI MachineLearning ReinforcementLearning NeuralNetwork QLearning DQN PPO A3C MultiAgent Automation Visualization PowerShell Education MLOps DeepLearning CNN RNN LSTM AutoML DataPipeline

PSEditions

Desktop

Dependencies

This module has no dependencies.

Release Notes

v3.0.0 (March 2026) - Full 8-phase ML framework complete. Phases 1-2: Neural Networks, Q-Learning, Dashboards. Phase 3: DQN, PPO, A3C. Phase 4: Supervised Learning. Phase 5: Data Pipeline. Phase 6: CNN, RNN, LSTM, Autoencoders, Transfer Learning. Phase 7: MLOps, Model Server, AutoML, Explainability. Phase 8: Tutorials, Examples, Templates.

FileList

Version History

Version Downloads Last updated
4.0.0 (current version) 4 3/19/2026
3.0.0 14 3/9/2026
2.1.0 9 3/1/2026
1.0.1 20 2/5/2026
1.0.0 3 2/4/2026