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Julia for Scientific Computing - Paperback

Julia for Scientific Computing - Paperback

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by Alexander Clifton (Author)

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.

Number of Pages: 268
Dimensions: 0.61 x 8.5 x 5.5 IN
Publication Date: November 18, 2024
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