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docs/01-Problem-Setup.html

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 <section id="curriculum" class="level2" data-number="1.2">
 <h2 data-number="1.2" class="anchored" data-anchor-id="curriculum"><span class="header-section-number">1.2</span> Curriculum</h2>
-<p>The course covers the framework of machine learning for predictive modeling and model interpretation from a practitioner’s perspective. You will be able to implement several popular machine learning techniques based on the question of interest and the dataset at hand. You will then evaluate the model based on their performance and diagnostics to understand its strengths and limitations. Technical mathematics and algorithms will not be emphasized.</p>
+<p>The course covers the framework of machine learning for predictive modeling and classification from a practitioner’s perspective. You will be able to implement several popular machine learning techniques based on the question of interest and the size and quality of dataset at hand. You will then evaluate the model based on their performance and diagnostics to understand its strengths and limitations. Technical mathematics and algorithms will not be emphasized.</p>
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 <section id="learning-objectives" class="level2" data-number="1.3">
 <h2 data-number="1.3" class="anchored" data-anchor-id="learning-objectives"><span class="header-section-number">1.3</span> Learning Objectives</h2>