步驟 6:部署模型
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您可以在 Google Cloud 中訓練、調整及部署機器學習模型。部署模型時,請注意以下重要事項:
- 請確保實際工作環境資料與訓練和評估資料的分佈相同。
- 收集更多訓練資料,定期重新評估。
- 如果您的資料分佈變動,請重新訓練模型。
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上次更新時間:2025-07-27 (世界標準時間)。
[null,null,["上次更新時間:2025-07-27 (世界標準時間)。"],[[["\u003cp\u003eGoogle Cloud provides a platform for training, tuning, and deploying machine learning models.\u003c/p\u003e\n"],["\u003cp\u003eMaintaining data consistency between training, evaluation, and production is crucial for optimal model performance.\u003c/p\u003e\n"],["\u003cp\u003eContinuous model improvement involves regular data collection, reevaluation, and retraining to adapt to evolving data distributions.\u003c/p\u003e\n"]]],[],null,["# Step 6: Deploy Your Model\n\nYou can train, tune, and deploy machine learning models on Google Cloud.\nPlease keep in mind the following key things when deploying your model:\n\n- Make sure your production data [follows the same distribution](https://developers.google.com/machine-learning/guides/rules-of-ml/?utm_source=DevSite&utm_campaign=Text-Class-Guide&utm_medium=referral&utm_content=rules-of-ml&utm_term=distribution#training-serving_skew) as your training and evaluation data.\n- Regularly re-evaluate by collecting more training data.\n- If your data distribution changes, retrain your model."]]