odjaramillo Critical Patterns
Model Development (REQUIRED)
# ✅ ALWAYS: Version your models and data
from datetime import datetime
model_config = {
"version": "1.2.0",
"trained_at": datetime.now().isoformat(),
"dataset_hash": compute_hash(training_data),
"hyperparameters": {...}
}
Reproducibility (REQUIRED)
# ✅ ALWAYS: Set seeds for reproducibility
import random
import numpy as np
import torch
def set_seed(seed: int = 42):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed_all(seed)
Decision Tree
Need classification? → Start with simple baseline
Need embeddings? → Use pre-trained models
Need fine-tuning? → Start with small learning rate
Need deployment? → Consider ONNX export
Need monitoring? → Track drift metrics
Resources
- ML Development: ml-development.md
- Cognee Integration: cognee/