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Julia for Scientific Computing
Overview
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.
This item is Non-Returnable
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Details
- ISBN-13: 9798230074601
- ISBN-10: 9798230074601
- Publisher: Northwood Lore Books
- Publish Date: November 2024
- Dimensions: 8.5 x 5.5 x 0.61 inches
- Shipping Weight: 0.76 pounds
- Page Count: 268
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