https://arshadhs.github.io/tags/models/Recent content in Models on Arshad SiddiquiHugoen-usTue, 21 Apr 2026 00:00:00 +0000https://arshadhs.github.io/docs/ai/machine-learning/99-ml-pipeline-model/Tue, 21 Apr 2026 00:00:00 +0000https://arshadhs.github.io/docs/ai/machine-learning/99-ml-pipeline-model/<h1 id="machine-learning-pipeline-preprocessing--models"> Machine Learning Pipeline: Preprocessing &amp; Models <a class="anchor" href="#machine-learning-pipeline-preprocessing--models">#</a> </h1> <p>This page explains both <strong>data preprocessing</strong> and <strong>model development concepts</strong> in a clear, structured way to support understanding.</p> <blockquote class="book-hint info"> <p>A complete ML pipeline includes preprocessing, feature engineering, feature selection, and model training.</p> </blockquote> <hr> <h1 id="1-data-preprocessing-overview"> 1. Data Preprocessing Overview <a class="anchor" href="#1-data-preprocessing-overview">#</a> </h1> <p>Raw data is often:</p> <ul> <li>Noisy</li> <li>Incomplete</li> <li>Inconsistent</li> </ul> <p>Preprocessing ensures data is suitable for machine learning.</p> <hr> <h1 id="2-missing-values"> 2. Missing Values <a class="anchor" href="#2-missing-values">#</a> </h1> <p><strong>Why they occur</strong></p> <ul> <li>Sensor errors</li> <li>Data collection issues</li> </ul> <p><strong>Methods</strong></p>