- Remove demonstrate_complex_computation_graph() function from Module 05 (autograd)
- Remove demonstrate_optimizer_integration() function from Module 06 (optimizers)
- Module 04 (losses) had no demonstration functions to remove
- Keep all core implementations and unit test functions intact
- Keep final test_module() function for integration testing
- All module tests continue to pass after cleanup(https://claude.ai/code)
- Fixed module 03_layers Tensor/Parameter comparison issues
- Fixed module 05_autograd psutil dependency (made optional)
- Removed duplicate 04_networks module
- Created losses.py with MSELoss and CrossEntropyLoss
- Created minimal MNIST training examples
- All 20 modules now pass individual tests
Note: Gradient flow still needs work for full training capability
- Added progressive complexity guidelines (Foundation/Intermediate/Advanced)
- Added measurement function consolidation to prevent information overload
- Fixed all diagnostic issues in losses_dev.py
- Fixed markdown formatting across all modules
- Consolidated redundant analysis functions in foundation modules
- Fixed syntax errors and unused variables
- Ensured all educational content is in proper markdown cells for Jupyter
IMPORT PATH FIXES: All modules now reference correct directories
Fixed Paths:
✅ 02_tensor → 01_tensor (in all modules)
✅ 03_activations → 02_activations (in all modules)
✅ 04_layers → 03_layers (in all modules)
✅ 05_losses → 04_losses (in all modules)
✅ Added comprehensive fallback imports for 07_training
Module Test Status:
✅ 01_tensor, 02_activations, 03_layers: All tests pass
✅ 06_optimizers, 08_spatial: All tests pass
🔧 04_losses: Syntax error (markdown in Python)
🔧 05_autograd: Test assertion failure
🔧 07_training: Import paths fixed, ready for retest
All import dependencies now correctly reference reorganized module structure.
PERFECT WORKFLOW: Clean lifecycle commands with distinct purposes
New Commands (No Overlaps):
✅ tito module start 01 → Start working on module (first time only)
✅ tito module resume 01 → Resume working on module (continue work)
✅ tito module complete 01 → Complete module (test + export)
✅ tito module status → Show progress with 3 states
Smart Features:
✅ State tracking: ⏳ not started → 🚀 in progress → ✅ completed
✅ Smart validation: start checks if already started, suggests resume
✅ Smart defaults: resume/complete work without module number
✅ Progress persistence: JSON file tracks started/completed modules
✅ Clear guidance: Always shows next logical step
User Journey:
1. tito setup → Environment setup
2. tito module start 01 → Begin tensors (marks as started)
3. Work in Jupyter, save → Natural development
4. tito module complete 01 → Test, export, mark completed
5. tito module start 02 → Begin activations
6. tito module resume 02 → Continue activations later
No command overlaps - each has distinct purpose and clear mental model!
