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https://github.com/MLSysBook/TinyTorch.git
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c59d9a116a
✅ Phase 1-2 Complete: Modules 1-10 aligned with tutorial master plan ✅ CNN Training Pipeline: Autograd → Spatial → Optimizers → DataLoader → Training ✅ Technical Validation: All modules import and function correctly ✅ CIFAR-10 Ready: Multi-channel Conv2D, BatchNorm, MaxPool2D, complete pipeline Key Achievements: - Fixed module sequence alignment (spatial now Module 7, not 6) - Updated tutorial master plan for logical pedagogical flow - Phase 2 milestone achieved: Students can train CNNs on CIFAR-10 - Complete systems engineering focus throughout all modules - Production-ready CNN pipeline with memory profiling Next Phase: Language models (Modules 11-15) for TinyGPT milestone
39 lines
968 B
YAML
39 lines
968 B
YAML
module:
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number: 0
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name: hello
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title: "Hello - Personalized Setup"
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description: "Interactive personalized setup with Rich CLI and system profiling"
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difficulty: "⭐"
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estimated_time: "30 minutes"
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learning_objectives:
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- "Set up personalized TinyTorch environment"
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- "Detect and understand system capabilities"
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- "Create interactive CLI experience"
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- "Configure development environment"
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prerequisites:
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- "Python 3.8+"
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- "Basic command line knowledge"
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exports:
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- "None (setup module only)"
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concepts:
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- "System profiling"
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- "Environment configuration"
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- "CLI interaction design"
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- "Development tool setup"
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ml_systems_focus:
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- "Hardware capability detection (CPU/GPU/RAM)"
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- "Environment optimization for ML workloads"
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- "Development workflow setup"
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success_criteria:
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- "Personalized configuration created"
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- "System capabilities detected"
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- "TinyTorch CLI working"
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- "Ready for Module 01"
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next_module: "01_tensor" |