when-training-neural-networks-use-flow-nexus-neurallisted

# Flow Nexus Neural Network Training SOP ```yaml metadata: skill_name: when-training-neural-networks-use-flow-nexus-neural version: 1.0.0 category: platform-integration difficulty: advanced estimated_duration: 45-90 minutes trigger_patterns: - "train neural network" - "machine learning model" - "distributed training" - "flow nexus neural" - "E2B sandbox training" dependencies: - flow-nexus MCP server - E2B account (optional for cloud) - Claude Flow hooks agents: - ml-developer (primary model architect) - flow-nexus-neural (platform coordinator) - cicd-engineer (deployment specialist) success_criteria: - Model training completes successfully - Validation accuracy meets requirements (>85%) - Performance benchmarks within thresholds - Cloud deployment verified - Documentation generated ``` ## Overview This SOP provides a systematic workflow for training and deploying neural networks using Flow Nexus platform with distributed E2B sandboxes. It covers architecture selection, distributed training, validation, and production deployment. ## Prerequisites **Required:** - Flow Nexus MCP server installed - Basic understanding of neural network architectures - Authentication credentials (if using cloud features) **Optional:** - E2B account for cloud sandboxes - GPU resources for training - Pre-trained model weights **Verification:** ```bash # Check Flow Nexus availability npx flow-nexus@latest --vers