feat(experiment-logger): add standalone logging framework

Create reusable experiment logging package with:
- UnifiedLogger for multi-backend logging (WandB, disk, stdout)
- Automatic checkpoint and model saving with metadata
- WandB artifact upload support
- Graceful degradation when WandB unavailable
- Comprehensive API documentation

This is a standalone, project-agnostic library that can be reused
across different ML projects.

src/experiment_logger/__init__.py

@@ -0,0 +1,11 @@
+"""Unified logging framework for machine learning experiments.
+
+This package provides a unified interface for logging to multiple backends
+(WandB, disk, stdout) simultaneously, ensuring no data loss.
+"""
+
+from experiment_logger.unified_logger import UnifiedLogger
+from experiment_logger.wandb_utils import finish_wandb, init_wandb
+
+__all__ = ["UnifiedLogger", "init_wandb", "finish_wandb"]
+__version__ = "0.1.0"