ml-course.html

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title: "Machine Learning with Python"
permalink: /courses/ml/
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    <h1 style="color: #4CAF50;">🤖 Machine Learning with Python</h1>
    <p style="font-size: 1.1em; color: #ccc;">
      This intermediate-to-advanced course covers core machine learning techniques, project workflows, and real-world modeling using Python, Scikit-learn, and Jupyter.
    </p>

    <h2 style="color:#00BFFF;">📘 What You'll Learn</h2>
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      <li>Supervised learning (regression, classification)</li>
      <li>Unsupervised learning (clustering, PCA)</li>
      <li>Model evaluation & selection (cross-validation, metrics)</li>
      <li>Feature engineering and pipelines</li>
      <li>Hands-on projects using Jupyter Notebooks</li>
    </ul>

    <h2 style="color:#00BFFF;">🧠 Course Format</h2>
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      <li>🖥️ Video Lessons & Quizzes</li>
      <li>📂 Downloadable Notebooks</li>
      <li>🎓 Capstone project: Predicting customer churn</li>
    </ul>

    <h2 style="color:#00BFFF;">📌 Requirements</h2>
    <p>Basic knowledge of Python, Pandas, and NumPy is expected.</p>

    <a href="/toolkits/" style="display:inline-block; margin-top:20px; background:#4CAF50; color:#fff; padding:12px 20px; border-radius:6px; text-decoration:none;">Start with Toolkits →</a>

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