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The marketing team at your organization has expressed the need to send biweekly scheduled emails to customers who are anticipated to spend above a variable threshold. This marks the marketing team's first foray into machine learning (ML), and you've been assigned the responsibility of overseeing the implementation. To address this requirement, you initiated a new Google Cloud project and leveraged Vertex AI Workbench to craft a solution that involves model training and batch inference using an XGBoost model, utilizing transactional data stored in Cloud Storage. Your goal is to establish an end-to-end pipeline that seamlessly delivers predictions to the marketing team in a secure manner while also optimizing for cost-efficiency and minimizing the need for extensive code maintenance. What steps should you take to achieve this objective?