<ul><li>Data scientists often face challenges with lengthy runtime of Python code when dealing with large datasets or complex ML/DL models.</li><li>Algorithm-based solutions like dimensionality reduction, model optimization, and feature selection can improve code efficiency.</li><li>Using a different programming language in certain cases can also help address the runtime challenge.</li><li>Practical techniques for reducing Python runtime are discussed using the Online Retail dataset as an example.</li></ul>

How to Reduce Python Runtime for Demanding Tasks

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