Julia for Scientific Computing

By: Clifton, Alexander

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.

• Format: Paperback
• Language: English
• ISBN: B0DP64562W
• ISBN13: 9798230074601
• Release Date: November 2024
• Publisher: Northwood Lore Books
• Length: 268 Pages
• Weight: 0.76 lbs.
• Dimensions: 0.6" x 5.5" x 8.5"