Hello PowerShell community,
I’ve published a development roadmap for VBAF (Visual Business Automation Framework), showing the planned evolution from educational RL framework to comprehensive ML toolkit—all in pure PowerShell.
What is VBAF?
VBAF implements machine learning concepts (neural networks, Q-learning, multi-agent systems) natively in PowerShell, designed specifically for IT professionals who want to understand ML fundamentals without switching to Python.
Current State (Phase 1 - Shipped):
- Neural networks with backpropagation
- Q-Learning with experience replay
- Multi-agent business simulations
- Real-time WinForms dashboards
- Available on PowerShell Gallery
Active Development (Phase 2):
Currently working on:
- Bug fixes and stability improvements
- Expanded test coverage
- Performance optimization
- Enhanced documentation
Planned Features (Phases 3-8):
The roadmap includes 34 features across multiple phases:
- Advanced RL algorithms (PPO, A3C, DQN)
- Supervised learning (regression, decision trees, clustering)
- Data preprocessing utilities
- Deep learning fundamentals (CNNs, RNNs)
- Production deployment capabilities
- Community education resources
View the Full Roadmap:
Project Board: https://github.com/users/JupyterPS/projects/2
All features are organized by phase with detailed descriptions and acceptance criteria.
Getting Started:
Install-Module VBAF -Scope CurrentUser
Import-Module VBAF
Get-VBAFExamples
Feedback Welcome:
The roadmap is community-driven. Feature requests, bug reports, and contributions are appreciated. Feel free to open issues on GitHub or discuss here.
Thanks for your time,
Henning