feat: implement training and deployment pipeline for LightGBM model on Mac to LXC

- Added comprehensive plans for training a LightGBM model on M4 Mac Mini and deploying it to an LXC container.
- Created scripts for model training, deployment, and a full pipeline execution.
- Enhanced model transfer with error handling and logging for better tracking.
- Introduced profiling for training time analysis and dataset generation optimization.

Made-with: Cursor

scripts/train_and_deploy.sh

@@ -0,0 +1,34 @@
+#!/usr/bin/env bash
+# 맥미니에서 전체 학습 파이프라인을 실행하고 LXC로 배포한다.
+# 사용법: bash scripts/train_and_deploy.sh [LXC_HOST] [LXC_MODELS_PATH]
+#
+# 예시:
+#   bash scripts/train_and_deploy.sh
+#   bash scripts/train_and_deploy.sh root@10.1.10.24 /root/cointrader/models
+
+set -euo pipefail
+
+LXC_HOST="${1:-root@10.1.10.24}"
+LXC_MODELS_PATH="${2:-/root/cointrader/models}"
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PROJECT_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
+
+cd "$PROJECT_ROOT"
+
+echo "=== [1/3] 데이터 수집 ==="
+python scripts/fetch_history.py --symbol XRPUSDT --interval 1m --days 90 --output data/xrpusdt_1m.parquet
+
+echo ""
+echo "=== [2/3] 모델 학습 ==="
+python scripts/train_model.py --data data/xrpusdt_1m.parquet
+
+echo ""
+echo "=== [3/3] LXC 배포 ==="
+bash scripts/deploy_model.sh "$LXC_HOST" "$LXC_MODELS_PATH"
+
+echo ""
+echo "=== 전체 파이프라인 완료 ==="
+echo ""
+echo "봇 재시작이 필요하면:"
+echo "  ssh ${LXC_HOST} 'cd /root/cointrader && docker compose restart cointrader'"