<p>Transform your data science workflows with Julia's lightning-fast performance. This practical guide helps Python and R developers transition to Julia for large-scale scientific computing machine learning and numerical analysis. Features real-world case studies optimization techniques and integration with popular data science tools. Includes parallel computing patterns and best practices for production deployment.</p>
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