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End-to-End Data Science Workflow Guide

The End-to-End Data Science Workflow explains how raw data is transformed into intelligent, real-world solutions. From defining business objectives and collecting data to preprocessing, model training, evaluation, and deployment, this guide covers every stage of a complete data science project lifecycle. Whether you are a beginner or an aspiring professional, understanding this structured workflow helps you build scalable, production-ready machine learning models that deliver measurable business value.