From Draft to Deployed: My Full Workflow for Building & Shipping a Predictive Modeling Product

See how a full predictive modeling product gets built and shipped.

Image by Author | Ideogram.ai

Building a robust predictive model is an iterative, end-to-end process that spans from understanding the business problem to monitoring a live model in production.

In this guide, I walk through each stage of the workflow for a predictive analytics project (e.g., churn prediction, sales forecasting, fraud detection), sharing best practices, tools, code snippets, and lessons learned. In the end, you will also get FREE Template to use for Building & Shipping a Predictive Modeling Product.

The focus would be on real-world constraints such as managing data quality, selecting the appropriate techniques, balancing complexity and interpretability, and avoiding common pitfalls like “garbage in, garbage out.”

Let’s get into it.

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